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Career Guidance, Scope & How to Become a Electronics and Communication Engineer After 12th

Career Guidance, Scope & How to Become a Electronics and Communication Engineer After 12th

Electronics and Communication Engineering (ECE) is about studying, designing, making, and using electrical circuits, electronics, and communication systems. ECE engineers work on many things, like phones, medical machines, and even things that fly in space.

Career Guidance, Scope & How to Become a Chemical Engineer After 12th

Career Guidance, Scope & How to Become a Chemical Engineer After 12th 

In the 1900s, chemical engineering mainly made chemicals. Then it joined with biology, so now it makes more things like plastics, stuff we use daily, fuel, medicine, food, and ways to help the environment. Nowadays, chemical engineers work in almost every job, using science and engineering to change basic stuff into things we need and enjoy. Learn the steps on how to become a chemical engineer and you can open  the door to a rewarding career in the world of science and technology.

Importance of Multidisciplinary Approach in Teaching - Learning

Importance of Multidisciplinary Approach in Teaching - Learning

 

Table of Contents 

 

Importance of Multidisciplinary Approach in Teaching - Learning

What Is Multidisciplinary Education?

Why Is a Multidisciplinary Approach in Education Important?

Multidisciplinary Education & National Education Policy  2023 (2020)

Benefits of Multidisciplinary Education

Job Benefits

Challenges to Multidisciplinary Education

Multidisciplinary Education @VIT, Pune

Frequently Asked Questions (FAQs)

 

Importance of Multidisciplinary Approach in Teaching - Learning

When you learn about many different things, you get a better understanding of how things work. When you mix ideas from different areas, you can come up with new ones. It's like making a new recipe by mixing different ingredients. Knowing about many different things gives you more ways to solve problems. And when you work with people who know different things, you learn from each other. So, a multidisciplinary approach in education is one of those things that help you gain knowledge from different areas. That's why multidisciplinary education is essential. This blog will discuss what it is, why it matters, its benefits, and how it can help your career.

 

What Is Multidisciplinary Education?

Let's consider a housewife. Instead of confining herself to traditional homemaking skills, she explores aspects such as nutrition, money management, interior design, human psychology, and effective time management. Now, let's see what the possible results could be.

By understanding nutrition principles, she ensured her family's meals were balanced and healthy, promoting their well-being.

Learning about budgeting, saving, and investing helped her manage household finances more effectively and ensure that resources were utilised optimally. Essentially, she learned about finance.

 

Knowledge of interior design helped her create a comfortable and aesthetically pleasing living environment for her family, enhancing their quality of life.

 

Understanding introductory psychology helped her in communication, conflict resolution, and understanding the emotional needs of her family members.

 

Time management techniques helped her efficiently juggle various responsibilities, balancing household chores, family commitments, and personal interests.

 

This approach is a multidisciplinary approach, where one learns within a specific field and gains knowledge across various disciplines. This enables individuals to utilise their diverse knowledge when facing problems or seeking solutions. This is multidisciplinary education.

Why Is a Multidisciplinary Approach in Education Important?

In the webinar held by, The Times Higher Education on November 2021. Raghav Gupta, managing director at Coursera, remarked, "Almost every business has said that they are going to digitise a lot more." He envisioned a future where every job role is going to require something more. 

 

A multidisciplinary approach to education is essential because it allows students to understand subjects comprehensively by incorporating knowledge and perspectives from various disciplines. 

 

Let’s see some examples - 

 


Developing new technologies often requires expertise from multiple disciplines. For instance, creating a smartphone involves knowledge of electronics engineering (hardware design), software engineering (programming), design (user interface), and marketing (identifying consumer needs and preferences). 








Similarly, suppose students are tasked with creating a sustainable solution for waste management in their community. A multidisciplinary approach would give a 360° perspective to the task and involve knowledge from environmental science (understanding the impact of waste on ecosystems), engineering (designing efficient waste disposal systems), economics (assessing the cost-effectiveness of different solutions), and sociology (considering the cultural and behavioural aspects of waste disposal).

Different disciplines offer unique perspectives and methodologies for understanding a problem. Students gain a more comprehensive and holistic understanding of the subject by integrating multiple disciplines.

 

A multidisciplinary approach in education better equips students to understand, analyse, and address the complexities of the world around them, preparing them to become well-rounded individuals and effective contributors to society.

Multidisciplinary Education & National Education Policy  2020

With the introduction of the National Education Policy 2020, India has taken significant strides in modernising its education system. This new approach to education aims to encourage the comprehensive development of individuals by getting into various fields of knowledge.

 

The NEP 2020 fully adopts this philosophy and efforts to reinforce it across all educational tiers. To achieve this goal, the policy describes several initiatives to promote a multidisciplinary approach to education.

 

Firstly, it advocates for promoting interdisciplinary studies across diverse educational institutions, encouraging collaboration among universities, colleges, research institutions, and other entities.

 

Secondly, the policy encourages the integration of traditional Indian knowledge systems into contemporary curricula, enriching the learning process with a holistic perspective on various subjects.

 

Lastly, the NEP urges the development of courses and programmes covering various disciplines, including mathematics, science, arts, technology, and humanities.

 

Multidisciplinary education constitutes a crucial component of India's modern educational framework. By this approach, the NEP 2020 aims to provide students with access to a broader knowledge base and skill set, equipping them for the dynamic challenges of the future.

 

A multidisciplinary approach enables students to examine topics from multiple angles, encouraging them to carve out their own independent opinions and viewpoints. The NEP 2020 aims to institutionalise multidisciplinary education across all educational levels in India, making it an integral part of the mainstream curriculum. By doing so, this approach will be accessible to a broader student base, nurturing a new generation of thinkers and innovators.

Benefits of Multidisciplinary Education

Multidisciplinary Education is like having a big toolbox filled with various tools for different jobs. Here's why it's helpful:

 

You look at the big picture

You see problems from different angles, like looking at a puzzle from various sides, which helps you understand things better.

 

You go outside the box  

Learning from different fields helps you develop new ideas because you're mixing different ways of thinking, like combining appropriate ingredients to make a new recipe.

 

You are ready for anything

Just like having different tools in your toolbox prepares you for different tasks, knowing about different subjects prepares you for different jobs or ventures. 

 

You solve problems better 

With knowledge from many areas, you have more ways to solve problems, like having more options to fix something when it breaks.

 

You work with others better 

You learn to work with people who know different things, just like how different tools work together to build something.

 

You start thinking critically 

You learn to question things and think for yourself, essential in making decisions and understanding the world.

Job Benefits 

Students with multidisciplinary backgrounds have the flexibility to explore a diverse array of career paths. Their varied personal and professional interests and the wide range of subjects available for study give them more opportunities in the job market. 

 

A multidisciplinary qualification equips individuals to navigate various career trajectories throughout their working lives. Research indicates that approximately a third of employers surveyed do not prioritise specific degree subjects when hiring graduates. This implies that multidisciplinary students can consider numerous career options and tailor their approach to work according to their diverse interests and skills.

Here are a few job roles that become much easier to pursue if you possess knowledge in various disciplines.

 

Job 

Role 

Advertising Agent

An advertising agent is a marketing professional responsible for selling advertising space to clients. 

Recruiter

A recruiter is a human resources professional who works to find and screen potential employees for companies. 

Management Consultant

A management consultant is responsible for providing expertise to help companies plan and implement projects. 

Project Manager

A project manager is responsible for each project stage from beginning to end. Professionals in this role can work in various fields, such as marketing, construction, and engineering. 

Account Director

An account director manages and maintains the relationship between the company and clients.

 

Challenges to Multidisciplinary Education

Multidisciplinary education undoubtedly offers numerous benefits. However, it also presents several challenges:

 

Curriculum Integration: Developing a unified curriculum that effectively integrates multiple disciplines can be challenging. Finding the right balance between depth and breadth of knowledge across different fields while ensuring continuity in learning experiences requires careful planning and coordination among educators.

 

Faculty Collaboration: Multidisciplinary education often requires collaboration among faculty members from different departments or schools. Overcoming disciplinary boundaries, separate research methodologies, and varying academic cultures can be difficult and may require additional training and support for faculty members.

 

Resource Allocation: Offering multidisciplinary programmes may require investments in resources such as faculty expertise and instructional materials. Allocating resources equally among participating disciplines while maintaining quality standards can be complex and challenging for educational institutions, especially when faced with budget constraints.

 

Assessment and Evaluation: Assessing student learning and evaluating the effectiveness of multidisciplinary programmes pose significant challenges. Traditional assessment methods may not adequately capture the skills and knowledge acquired through interdisciplinary approaches. 

Multidisciplinary Education @VIT, Pune  

VIT, Pune, adopts a multidisciplinary approach to teaching and learning, as per the guidelines of AICTE and NEP-2020, regardless of the engineering branch. Thus, it is crucial to provide advanced technological knowledge to all students. Consequently, encouraging this multidisciplinary approach in faculty and students of higher educational institutions becomes imperative.

 

Another aspect of VIT's educational model is the mandatory implementation of a multidisciplinary approach for all students, irrespective of their branch, in Module 3, which is in semester 2. VIT, Pune, has established an independently functioning Department of Multidisciplinary Engineering since AY 2020-21, a first in Maharashtra and India as well, emphasises the importance of the multidisciplinary approach due to various reasons:

 

  • It aligns with the requirements set forth by AICTE and NEP-2020.
  • It transcends the boundaries of specific branches of engineering.
  • It ensures that all students are equipped with up-to-date technological knowledge.
  • It meets the demands of the contemporary industry.
  • It enhances placement opportunities, as companies prefer candidates capable of applying core knowledge across diverse domains.
  • It enables students to tackle and resolve societal issues effectively, as recognised by the National Board of Accreditation (NBA).

Additionally, Students can enroll in Value-Based Courses at the beginning of Semester 1, Module 1. The value-based courses continue throughout their subsequent semesters. 

Frequently Asked Questions (FAQs)

Q.1 How does multidisciplinary education relate to the National Education Policy 2023?

The National Education Policy 2020 (NEP 2023) encourages comprehensive development by promoting a multidisciplinary approach across all educational tiers. It advocates for interdisciplinary studies, integrating traditional Indian knowledge systems, and developing courses covering various disciplines.

Q.2 How does multidisciplinary education differ from traditional education?

Traditional education often focuses on specialised knowledge within a single discipline, while multidisciplinary education encourages exploring and integrating knowledge from multiple fields. Multidisciplinary education aims to provide a broader and more holistic understanding of topics.

Q.3 Why is multidisciplinary education necessary in today's world?

Multidisciplinary education prepares individuals to tackle different challenges in an increasingly interconnected and complex world. It cultivates critical thinking, creativity, and adaptability, essential skills for addressing real-world problems and driving innovation across various domains.

Q.4 What role does technology play in facilitating multidisciplinary education?

Technology enables access to diverse resources, facilitates collaboration across geographical boundaries, and supports innovative teaching and learning methods. Online platforms, digital tools, and multimedia resources can enhance multidisciplinary education by providing interactive and immersive learning experiences.

 

Q.5 How does multidisciplinary education contribute to personal and professional development?

Multidisciplinary education contributes to personal and professional development by enhancing problem-solving skills, broadening perspectives and providing versatility in career opportunities. This approach encourages individuals to draw upon diverse knowledge and perspectives, equipping them with the skills and mindset needed to thrive in a dynamic and interconnected world.

 

 

Artificial Intelligence vs Data Science vs Machine Learning

Artificial Intelligence vs Data Science vs Machine Learning

Over the past few years, the popularity of Artificial Intelligence (AI), Machine Learning, and Data Science has risen to such an extent that most companies have now engaged in their digital transformation journey toward a fully connected factory or Industry 4.0.

 

Simply put, Data science, machine learning, and artificial intelligence (AI) are interconnected fields that combine to extract insights from data, make predictions, and automate decision-making processes. 

What is Data Science?

When you shop online, have you noticed how the platform suggests products similar to the ones you've viewed or purchased before? This is made possible through data science. Algorithms analyse your past purchases, browsing history, and even demographic information to predict what products you might be interested in, thus enhancing your shopping experience.

 

Data science involves extracting insights and knowledge. It combines elements of mathematics, statistics, computer science, and domain knowledge to analyse large volumes of data and extract meaningful patterns, trends, and insights. Data science encompasses various techniques, including statistical analysis, machine learning, data mining, and visualisation.

 

How is the Data Science Foundation for AI?
Data science plays a crucial role in AI by providing the necessary tools and techniques to analyse and derive insights from data. AI systems often rely on large volumes of data to learn and improve their performance, and data science helps in preprocessing, cleaning, analysing, and interpreting this data to extract meaningful patterns and insights.

 

Imagine you work for a retail company that wants to improve its sales strategy using artificial intelligence (AI). The company collects vast amounts of data, including sales transactions, customer demographics, website interactions, and social media mentions. Through data analysis, the retail company might discover that customers who purchase certain types of clothing are more likely to buy accessories if they receive personalised recommendations based on their previous purchases. With this insight, the company can develop AI-powered recommendation systems to suggest relevant products to customers, ultimately boosting sales.

 

Role of  Machine Learning in AI?
Machine learning is a subset of AI that focuses on developing algorithms and models that enable computers to learn from data and improve their performance without being explicitly programmed. Many AI systems employ machine learning techniques to analyse data, make predictions, and adapt to new information, making it a fundamental component of AI.

 

For the same retail company, once they receive the data,  data scientists use various analytical techniques to extract valuable insights. They may employ machine learning algorithms to identify patterns in customer behaviour, such as which products are frequently purchased together or which marketing campaigns are most effective for different demographic groups.

 

Understanding Through a Case Study 

There is an online retail company specialising in fashion apparel. They want to enhance customer engagement on their website and increase sales by providing personalised recommendations to their customers. Now let’s see how Data Science, AI and Machine Learning can help them. 

 

Data Science - The data science team starts by collecting and analysing vast customer data, including browsing history, purchase history, demographics, and social media interactions. They use statistical analysis and data visualisation techniques to identify patterns and trends in customer behaviour.

 

Machine Learning - With the insights gained from data analysis, the machine learning team develops algorithms to predict customer preferences and recommend products tailored to individual interests. They train these algorithms using supervised learning techniques, continually refining them based on real-time feedback and customer interactions.

 

Artificial Intelligence (AI) - The company integrates AI-powered chatbots into its website. These chatbots use natural language processing algorithms to interact with customers in real time, providing personalised recommendations, answering questions, and addressing concerns. The chatbots learn from each interaction, becoming more efficient and accurate over time.

 

Results - The company successfully improves customer engagement and boosts sales by using data science, machine learning, and AI. Customers receive personalised recommendations that align with their preferences, leading to increased satisfaction and loyalty. The AI-powered chatbots enhance the shopping experience by providing instant assistance, ultimately driving higher conversion rates and revenue for the company.

 

Difference between AI, Data Science and Machine Learning 

 

 

Data Science 

Artificial Intelligence 

Machine Learning 

Function 

Analysing raw data to find important information for making smart decisions.



Helps machines do difficult things like humans, such as making decisions and solving problems, effortlessly



Builds a system for computers to learn from data and get better at their tasks over time by using the knowledge gained.



Application

Businesses can use it to solve tricky problems, spot trends, and predict future market conditions.

It can be applied in chatbots, for providing voice assistance and in robots to carry out tasks usually done by humans.



It can be employed to create automated recommendations, search algorithms, and health monitoring systems that learn from the data.




Required Skills and Competencies

Proficiency in advanced mathematics, statistics, database management, data visualisation, and a fundamental grasp of machine learning methods.

Proficiency in advanced mathematics, knowledge of programming languages (particularly Python, R, Java, and C++), an understanding of probability and statistics




Understanding of neural network architectures, expertise in data modelling and evaluation, and a foundational grasp of natural language processing.






Study CSE - Artificial Intelligence & Machine Learning from VIT Pune 

 

Studying B.Tech in Computer Science and Engineering with a specialisation in Artificial Intelligence & Machine Learning at VIT Pune offers a comprehensive and cutting-edge educational experience. Through theoretical knowledge and hands-on practical learning, students delve deep into AI and ML, exploring algorithms, data structures, neural networks, and more. The program at VIT Pune is designed to equip students with the skills and expertise needed to tackle real-world challenges in AI and ML, preparing them for careers in diverse industries such as technology, finance, healthcare, and beyond. With world-class faculty, state-of-the-art infrastructure, and industry collaborations, VIT Pune provides a dynamic learning environment where students can thrive and innovate in the exciting field of artificial intelligence and machine learning.

Frequently Asked Questions (FAQ’s)

 

  • What are the critical applications of AI, Data Science, and Machine Learning?

AI can be applied in various domains, such as chatbots, voice assistance, and robotics. Data Science solves business problems, spot trends, and predicts market conditions. Machine Learning builds systems that learn from data and improve tasks over time.

 

  • What skills are required for a Data Science, AI, and Machine Learning career?

Proficiency in mathematics, statistics, and programming languages (such as Python or R) and an understanding of algorithms and data structures are essential for careers in these fields.

 

  • What are the ethical considerations associated with AI and data-driven decision-making?

Ethical considerations include data bias, privacy concerns, the transparency and accountability of AI systems, and the potential impact on employment and societal norms.

 

  • What are some real-world examples of AI applications in everyday life?

Examples include virtual assistants like Siri and Alexa, recommendation systems on platforms like Amazon and Netflix, and autonomous vehicles.

 

  • What are the main techniques used in Data Science? 

Data Science encompasses various techniques, including statistical analysis, machine learning, data mining, and visualisation.

What Is the Difference Between Computer Science & Information Technology?

What Is the Difference Between Computer Science & Information Technology?

Feeling confused about your career path in computer science or information technology? You're not alone. It's common for people to struggle with the difference between CS and IT engineering and often mistake one for the other. However, you cannot be stuck in such confusion when making a career decision. You need clarity. So, in this blog, we'll assist you in understanding the difference between CS and IT engineering, the required skills for each, how to pursue them, suitable career options, and the respective salaries so that you can choose your career wisely. 

The difference between CS and IT can be blurred. Sometimes, IT jobs need computer science knowledge, and programming tasks can seem like IT work. Jobs which rely on computer science, like web development or software engineering, can also be called IT work. This can all make things confusing.

Difference Between IT and Computer Science?

Let’s keep it simple, using real-life examples. Think of computer science as a chef cooking new recipes and information technology as a restaurant manager running a successful restaurant. 

As a chef experiments with different ingredients and cooking techniques to create new dishes, computer engineers explore algorithms, data structures, and programming languages to develop innovative software solutions. They focus on understanding the fundamental principles of computing and pushing the boundaries of what's possible in technology.

Similar to how a restaurant manager ensures the smooth operation of a restaurant, information technology professionals manage and maintain computer systems, networks, and software applications to support the daily operations of businesses and organisations. They focus on implementing and optimising existing technologies to meet users' needs and requirements.

Is Information Technology a part of Computer Science?

Imagine computer science as a vast ocean encompassing many concepts, theories, and applications related to computing. Within this ocean is a smaller body of water called information technology, a subset of computer science.

Computer Science is like a big umbrella covering everything about computers and their work. It's about designing, making, and using them for various things. On the other hand, Information Technology (IT) is more about using computers to solve real-life problems. IT people are the ones who make sure computer networks run smoothly, create software, and help people when they have technical issues. Even though IT is a part of Computer Science, they have a lot in common and share many basic ideas.

What Skills Do You Need for a Career in Computer Science and IT?

 

Computer Science 

Information Technology 

Programming languages like Python, C++, HTML, CSS, Javascript

Programming languages, especially scripting languages like Python and Powershell

Statistics, algebra, and/or calculus

Troubleshooting methods

Familiarity with code-sharing platforms like GitHub

Network configuration

Understanding of the software development lifecycle

Security infrastructure like setting up firewalls and routers

Artificial intelligence methods like machine learning and deep learning and tools like Apache Spark and Hadoop

Ethical hacking or penetration testing

Data analysis and database tools like SQL, MongoDB, PostgreSQL, Excel

Data administration skills like SQL

 

How do you build your career in information technology and computer science?

In Computer Science, a bachelor’s degree is typically the standard educational requirement for entry-level positions, providing a comprehensive understanding of computing principles and programming languages. However, individuals seeking to go deeper into specialised areas or aspire to leadership roles often pursue degrees such as a Master of Science in Computer Science or a PhD. These advanced programs offer opportunities to explore advanced topics like machine learning, software engineering, or computer architecture, equipping graduates with the expertise needed to tackle complex challenges and drive innovation in the field. 

Individuals entering the Information Technology (IT) field start with a bachelor’s degree. This level of education provides a solid foundation in computer science principles and practical skills necessary for entry-level positions in the industry. However, for those aiming for more competitive or specialised roles, pursuing advanced degrees like a Master of Science in Computer Science can be advantageous.

IT vs Computer Science Salary and Career Opportunity

 

Computer Science Roles 

Salaries 

Information Technology Roles 

Salaries 

Web developer

INR 4.5 LPA 

Cybersecurity specialist

INR 11.8 LPA 

Full stack developer

INR 9.2 LPA 

Cloud engineer

INR 7.2 LPA

Software engineer

INR 8.6 LPA

Network administrator

INR 5.6 LPA 

Robotics engineer

INR 3.9 LPA

Database administrator

INR 12.4 LPA

Back end engineer

INR 8.8 LPA

System administrator

INR 5.1 LPA

Data scientist

INR 14.4 LPA 

Helpdesk technician

INR 2.1 LPA

Artificial intelligence engineer

INR 11.7 LPA

Computer technician

INR 2 LPA 

 

Computer Science and Information Technology in VIT 

At Vishwakarma Institute of Technology (VIT), Pune, the landscape of Computer Science and Information Technology (IT) education has evolved since its inception. The institution introduced its undergraduate program in Computer Engineering in 1991, followed by the launch of the postgraduate course in 2001. Notably, the doctoral program in Computer Engineering was established in 2011, marking a significant milestone in academic offerings. Led by distinguished faculty members like Prof.(Dr.) S. R. Shinde and Prof. (Dr.) P. P. Ghadekar, the departments have consistently nurtured a culture of academic excellence and practical application. With undergraduate intakes of 240 and 180 students for Computer Science and Information Technology, respectively, VIT. Pune has a strong faculty-student ratio, ensuring personalised attention and mentorship. The faculty members, renowned for their professional expertise, engage students with real-world insights and hands-on learning experiences, providing a dynamic and enriching educational environment. This commitment to quality education and holistic development underscores VIT Pune’s position as a premier Computer Science and Information Technology institution.

 

What’s for AI in 2024?

As we enter 2024, the world of innovative technology is moving faster than ever, and something called "generative AI" is making a big move. Last year, people got a taste of it with things like ChatGPT. But get ready because 2024 is all about businesses and big industries jumping on the generative AI to make things better and more intelligent. So let's see what AI for future looks like and what are AI predictions for the future. Also, let us look at “Is AI good for the future?

As per the CIO&Leader Annual State of Enterprise Technology report, the adaptability of artificial intelligence (AI) is encouraging businesses to explore a wide range of applications within their daily operations. This trend is sparking increased enthusiasm for integrating AI in various business processes.

As reported by Indian Business Insider, “The marked increase in AI spending reflects a fundamental shift in enterprise technology investment strategies. It highlights the growing realisation of the transformative impact of AI on business operations and its tangible benefits," said R Giridhar, Group Editor and Head of Research at 9.9 Group.

Let's explore some territories where artificial intelligence (AI) has the potential to make significant advancements.

AI in 2024: What to Expect

ChatBots 

When we talk about AI predictions for the future, this is the first thing that comes to mind. In 2024, generative AI is expected to become more accessible to the everyday person, even those without technical expertise. We anticipate a surge in individuals experimenting with a multitude of AI models. Advanced AI models like GPT-4 and Gemini are at front runners, being multimodal and capable of handling text, images, and videos. However, the effectiveness of this trend depends on the reliable performance of these models. With the ability to handle diverse types of content, chatbots can interact with users through text, images, and even videos. This richer, more dynamic interaction is poised to create a more personalised and interactive communication experience.

Moreover, the multimodal capabilities of AI models like GPT-4 and Gemini empower chatbots to generate text-based responses and visual content. Chatbots can create and share images or graphics, offering a more comprehensive and visually appealing communication experience.

Turn Words into Videos 

Imagine a magical world where computers can turn words into videos. Cool, right? Tools like OpenAI's DALL-E, Stability AI's Stable Diffusion, and Adobe's Firefly are making this happen. They've flooded the internet with mind-blowing pictures, and now they're stepping up their game to create videos from plain text.

Big movie studios like Paramount and Disney are taking notice and using these cool computer tricks in their movies. They're making actors' voices match up perfectly with different languages and doing mind-blowing things with special effects. It's not just for film; many big companies also use this tech for advertising and training. 

Professional Licensing for AI

In the following year, we may require AI systems to get a professional license,” said Amy Webb, chief executive of the Future Today Institute, a consulting firm. “While certain fields require professional licensing for AI, so far, algorithms get to operate without passing a standardised test. You wouldn’t want to see a urologist for surgery who didn’t have a medical license in good standing, right?”  In the world of AI, we wonder if it's necessary to have a license because AI can be used for good and bad things. On the positive side, it can help a lot in areas like healthcare, education, and taking care of the environment. But if it's misused, it could cause problems like invading privacy, maltreating people, taking away jobs, and the risk of AI-powered weapons. Professional licensing for AI can act as a control to balance the significant authority humans hold.

The importance of authenticity will grow even more

Imagine being sure whether your friend's vacation photo on Instagram is a real-life moment or created by a computer. There's a prediction that Apple will introduce a "Photographed on iPhone" stamp next year to confirm that the photos are not generated by artificial intelligence. As we navigate an era where AI's capabilities expand, establishing trust and veracity in our interactions, communications, and shared experiences will become essential to preserving the integrity of our digital narratives and connections.

Future Jobs for Specialization in AI

When thinking about jobs in AI, we wonder, "What are the future jobs for specialisation in AI?

The job market for AI is changing a lot. Some jobs might disappear, but there are new chances coming up, especially in fields that need advanced AI and data skills. This change is important for India. By 2024, around 1.2 million AI-related jobs might not have anyone to do them. It's crucial for people in India to learn new skills and keep learning. This shift in the job market gives a significant opportunity for professionals in India to change and do well in the growing AI job market. It's a great time for professionals to learn more, keep learning, or even think about switching to a career in AI.

Future AI Scope in India and the World

In 2024, the stories of AI around the world and in India are coming together. Global trends like practicality, open-source models, regulations, job changes, and efficiency improvements are causing big changes in AI. Meanwhile, India's growth in IT and AI brings a special touch to this story. India has a big market, lots of investments in IT and AI, and new rules, making it stand out in the global AI revolution. Going into 2024 and beyond isn't just about adapting to changes; it's about leading and shaping the future of technology and innovation. Let's go on this exciting journey together!

Exploring the Growing Demand for AI Engineers

Exploring the Growing Demand for AI Engineers

 

AI engineers are in high demand for good reason. The world is in a transformative era driven by the potential of Artificial Intelligence (AI). As reported by The Economic Times, “By 2030, AI is poised to contribute a staggering $15.7 trillion to the global economy, surpassing the combined outputs of economic giants China and India”. The individuals who possess the skills to navigate through this complex domain (AI Engineering) are going to be in high demand. 

In the digital age, where technology is the driving force behind innovation and progress, pursuing a degree in Computer Engineering and Artificial Intelligence (AI) is becoming a good career option. New AI tools like ChatGPT, Bard, MidJourney, and others are making people worried about future jobs.

But how can you become an AI engineer? What do you need to do to get into this growing field, and what is the AI Engineer salary in India? Let's explore all these aspects together and find out why getting a degree in Computer Engineering and AI is a smart decision. 

 

Who is an AI Engineer?

An AI engineer is someone who improves artificial intelligence by using programming and data science. They work on things like machine learning and neural networks and help make sure AI is used responsibly by companies all over the world.

 

What does an AI Engineer do?

An AI engineer is someone who makes computers smart. They create programs and systems that help machines do things that usually need human intelligence. They can specialise in areas such as natural language processing, computer vision, or reinforcement learning, depending on their expertise and project requirements. Additionally, AI engineers collaborate with cross-functional teams, analyze data, and stay abreast of the latest advancements in AI technology to ensure the effective integration of AI solutions into various applications and industries.

 

How can you become an AI Engineer?

Step 1: Obtain a bachelor's degree.

You can opt for Computer Sciences & Engineering (Artificial Intelligence) or Computer Sciences & Engineering (Artificial Intelligence & Machine Learning) course. The specific curriculum for Computer Science and Engineering programs focusing on Artificial Intelligence (AI) or Artificial Intelligence and Machine Learning (AI/ML) can vary across institutions. This course gives you a basic understanding of how these technologies work and where they're used. You'll learn the theoretical basics of AI, like logic, search algorithms, and different types of machine learning models.

 

Step 2: Earn Certifications

Getting certified in Artificial Intelligence (AI) or Artificial Intelligence and Machine Learning (AI/ML) is like having a special badge that shows you're good at these fast-growing technologies. It's not just about learning in a structured way; having these certificates makes you stand out when looking for a job. Companies and important people in the field know and respect these certificates, which can help you make important connections and move forward in your career. So, getting certified isn't just about learning; it's like getting a key to more opportunities and a way to show everyone that you know your stuff in AI or ML.

 

Step 3: Acquire Practical Experience 

To be an AI engineer, it's important to do things. it's also crucial to work on real problems. By doing projects and joining hackathons, you can learn practical skills and get hands-on experience with the tools and technologies used in AI engineering. Knowledge of AI tools like ChatGPT can greatly benefit computer engineers by offering versatile applications in their work. These tools can be employed to automate customer support through the creation of intelligent chatbots, streamlining query resolution. Additionally, computer engineers can leverage AI for code assistance, automating tasks like code generation and debugging.

 

AI Engineer Salary

Glassdoor reports that the typical yearly income for an AI engineer in India is ₹765,353 and in the United States is $114,121. Salaries can vary across different companies and depend on the skills and expertise you possess.

 

Some AI Engineering Professions:

Profession 

Description 

AI Developer 

An AI developer collaborates closely with electrical engineers, creating software to bring artificially intelligent robots to life.

AI Architect 

AI architects work closely with clients to help with business and system integration. They also create and take care of the entire architecture.

Machine Learning Engineer 

ML engineers make models that predict things using lots of data. They know a lot about machine learning and deep learning algorithms and frameworks.

Data Scientists 

Data scientists collect, clean, and make sense of big, complex data using machine learning and predictive analytics.

Business Intelligence Developer 

They design, model, and analyze complex data to find out what's happening in business and the market.



 

Why Learning AI Now Gives You a Big Advantage?

 

The fast progress of AI, seen in amazing models like GPT-4 and DALL-E3, has changed what AI can do. These models create clear writing and lifelike pictures, showing how AI can help in different areas. However, using and improving these models well needs a special kind of expert, and those experts are AI engineers. The field of Computer Engineering and AI is synonymous with innovation. Graduates of this field find themselves at the front of technological changes, contributing to the development of intelligent systems & algorithms. The knowledge in this dynamic field ensures constant exposure to the latest technologies, making graduates valuable assets in the fast-changing industry.

 

Frequently Asked Questions (FAQs)

 

1. What is the role of an AI Engineer?

 

Answer: An AI engineer enhances artificial intelligence through programming and data science. They focus on areas such as machine learning neural networks and ensure companies' responsible use of AI globally.

 

2. What tasks does an AI Engineer typically perform?

 

Answer: AI engineers create programs and systems to make machines perform tasks requiring human-like intelligence. They specialise in natural language processing, computer vision, and reinforcement learning. They also collaborate with cross-functional teams, analyse data, and stay updated on AI advancements.

 

3. How can practical experience benefit an AI Engineer's career?

 

Answer: Practical experience gained through projects and hackathons is crucial for AI engineers. It provides hands-on skills with AI tools like ChatGPT and helps solve real-world problems. Practical knowledge is essential for success in the field.

 

4. What is the average salary of an AI Engineer in India and the United States?

 

Answer: According to Glassdoor, the typical yearly income for an AI engineer in India is ₹765,353, while in the United States, it is $114,121. Salaries may vary based on skills, expertise, and the employing company.

 

5. Why does learning AI now provide a significant advantage?

 

Answer: The rapid progress of AI, exemplified by models like GPT-4 and DALL-E3, has expanded its capabilities. Learning AI now provides a big advantage as it requires specialised experts—AI engineers—to effectively use and enhance these advanced models.

Can a Chemical Engineer Become a Software Engineer?

  • can a chemical engineer become a software engineer

 

We are confused about many career options in this era of confusing career choices. Even if we choose engineering as a career option, we are confused about which branch to choose. 

 

At times, even if we choose a different career, we might end up with a job that doesn't excite us, and we wish we could change what we do. Many people want to switch jobs within the field of engineering.

 

Let's put some light on switching from chemical engineering to computer science.

 

Transition from Chemical Engineer to Software Engineer

 

If you’re looking for an answer to the question, Can a chemical engineer become a software engineer? This blog is for you. In this blog, we will guide you to transform your career and explore the skills, challenges, and opportunities for your way to success in computer engineering. 

 

First, what skills do you have in your bank that you have acquired during chemical engineering?

 

The mindset should be to utilise those skills in developing the ones needed for computer engineering. So let’s begin….

 

1. Use Chemical Engineering Expertise

 

  • Analytical Mindset

Chemical engineers are equipped with an analytical mindset, a skill crucial in software development. The ability to break down complex problems into easier components is a unique skill, making you a solid candidate for transition.

 

  • Problem-Solving Skill

One of the traits of a chemical engineer is their problem-solving skills. This skill smooths your transition into the software engineering domain, where identifying and rectifying bugs, optimising code, and troubleshooting are everyday challenges.

 

  • Process Optimization in Software Development

Chemical engineers are very good at optimising processes, a skill easily transferable to software development. It can be used in code deployment and streamlining development workflows.

 

2. Master Algorithmic Thinking

 

Software engineering is fundamentally algorithmic. Chemical engineers can use their mathematical powers to understand and implement algorithms efficiently. Platforms like HackerRank and LeetCode provide an excellent playground for learning these skills.

 

  • Coursera

  • Learn to code with me 

  • Enjoy Algorithms

  • Learning.com

3. Get Into Web Development

 

Learning web development is a strategic move for those eyeing a career in software engineering. Learning front-end technologies like HTML, CSS, and JavaScript broadens the skill set and enhances the adaptability of a transitioning professional.

 

4. Networking and Mentorship

 

Building a network within the software engineering community is a very important step. Engaging with forums like GitHub and participating in coding communities will allow you to collaborate. You can seek mentorship in these communities, too.

 

5. Continuous Learning 

 

The most important thing of all is that you should have a flexible and continuous Learning Mindset. Transitioning from chemical engineering to software engineering demands a commitment to continuous learning. The tech industry evolves daily, and staying updated on emerging technologies and industry trends is very important.

 

10 Places to learn Programming and Coding for FREE

 

Platform 

About 

Udemy 

Online courses in all the latest technology and programming languages like Java, Spring, Data Structure and Algorithms, Selenium, REST, etc. It provides both free and paid resources.

Educative

Online courses like Grokking the System Design Interview and Grokking the Coding Interview: Patterns for Coding Questions

Coursera

Online courses from Universities like Stanford, University of London, University of Michigan, Colorado, Imperial College of London and many more.

FreeCodeCamp

Massive collection of interactive tutorials and exercises to learn JavaScript, Data Structure and Algorithms, Frontend Development

Pluralsight 

Learn any technology or IT courses like programming language like Java, Web development framework like Spring Framework, Hibernate, etc.

GitHub

Learn Git online like Git branching which will teach you Git commands right from your web browser.

Onemonth.com

Learn Python, Ruby, and JavaScript in 30 days, and they teach in a boot camp style which makes it a very effective learning place.

Codecademy.com

Learn some of the most popular technologies like JavaScript, Java, and Linux for free. It also has some paid courses to learn advanced concepts in Python, Java, and JavaScript.

codingbat.com

Learn a lot of free programming exercises to build coding sense in both Python and Java.

code.org

Start learning coding and the basics of computer science. My kids use this website to learn to code by playing with the Minecraft game

 

What Else Can You Do?

 

Many people in India often opt to pursue a Master's degree or take a conversion course in software development while still in college. After completing your bachelor's degree, you can choose to do a one-year Master's program to gain fundamental knowledge in software development.

 

More and more people are teaching themselves how to code. In the tech world, companies care more about your work experience and references than whether you have a Software Engineering Degree. This means that bright minds who didn't do software engineering can still do well in the industry.

 

But going the self-taught route takes a lot of time and dedication. You have to be disciplined and organised in how you approach it.

 

Believe you can have a seamless transition

 

Can a chemical engineer become a software engineer? The answer is yes, and it fills you with many opportunities. If Chemical Engineers can use their analytical skills, develop coding proficiency, and commit to continuous learning, they can successfully walk through this transformative path. With a keen eye for detail, chemical engineers are well-suited for quality assurance and testing roles. Also, the data-centric nature of chemical and software engineering brings them into the world of Data Science.

Top 5 Career Options After Electronics & Communication Engineering

Top Career Option After Electronics & Communication Engineering

 

Electronics and communication engineering is like having a big menu with many choices for your career. There are a lot of electronics and communication engineering jobs. This field covers radio, internet, satellites, and wireless phones. You learn to make these things and study, analyse, and improve how you already communicate using them.

 

What are Opportunities for Electronics and Communication Engineers?

 

According to The Bureau of Labour Statistics, ECE engineers will have a 7 percent year-on-year demand. The recruitment figures will reach over 345,800 by 2026, which is a massive number and a reason enough for aspiring engineers to pursue a career in ECE.

 

Let’s look at some of the best electronics and communication engineering jobs.

 

  • Wireless Communications Engineer

Role as Wireless Communications Engineer

 

After graduating, one of the best career options is to be a Wireless Communication Engineer. As Wireless Communication Engineers, you create, set up, and care for wireless communication systems. They ensure wireless connections work well and are dependable for different uses and businesses. They deal with technologies like mobile networks, Wi-Fi, Bluetooth, satellite communications, and so on.

 

Role as Wireless Communications Engineer

 

Wireless Communications Engineer Salary

 

The salary for a Wireless Network Engineer in India varies from ₹1.7 Lakhs to ₹13.5 Lakhs, with an average annual salary of ₹5.0 Lakhs.*

 

*Source - Ambitionbox

 

  • Hardware Engineer

 

Role as Hardware Engineer

 

Hardware Engineers are the ones who plan, create, and check the parts and systems that make computers run. This makes it an interesting career option. They concentrate on computer systems, built-in systems, and electronic gadgets, getting involved in making hardware, like designing circuits, arranging circuit boards, making prototypes, testing, and fixing issues.

 

Role as Hardware Engineer

 

Hardware Engineer Salary

 

The salary for a Hardware Engineer in India ranges from ₹0.8 Lakhs to ₹12.9 Lakhs, with an average annual salary of ₹6.9 Lakhs.

 

*Source - Ambitionbox

 

  • Telecom Engineer

 

Role as Telecom Engineer

 

A Telecom Engineer manages the analysis and design of new technologies to benefit customers and researches ongoing services to improve facilities. Telecom is crucial in almost every industry globally, making it a highly sought-after field known for its reliability in the years to come.

 

Role as Telecom Engineer

 

Telecom Engineer Salary

 

The salary for a Telecommunication Engineer in India ranges from ₹1.2 Lakhs to ₹15.0 Lakhs, with an average annual salary of ₹4.6 Lakhs.

 

*Source - Ambitionbox

 

  • Software Analyst

Role as Software Analyst

 

A software analyst's role involves running, designing, creating, and testing new and existing software for an organization. This includes acting as a mediator between software users and developers. The primary responsibility is to adapt the software's algorithms to meet customer requirements and continually update or modify them for enhanced user-friendliness. Individuals in this role may explore career options in project management, quality assurance, or system architecture, leveraging their expertise in software analysis to contribute to various aspects of the software development lifecycle.

 

Role as Software Analyst

Software Analyst Salary

 

The salary for a Software Analyst in India varies from ₹2.5 Lakhs to ₹12.0 Lakhs, with an average annual salary of ₹6.8 Lakhs.

 

*Source - Ambitionbox

 

  • Robotics Engineer

 

Role as Robotics Engineer

 

Robotics engineers are responsible for designing, developing, and taking care of robotic systems. They combine mechanical engineering, electrical engineering, computer science, and artificial intelligence principles to create smart machines.

 

Role as Robotics Engineer

 

Robotics Engineer Salary

 

Robotics engineering salary in India ranges from ₹1.8 Lakhs to ₹8.2 Lakhs, with an average annual salary of ₹3.8 Lakhs.

 

*Source - Ambitionbox

 

Job Opportunities for Electronics and Communication Engineers in the Government Sector

 

Public service companies recruit electronics and communication engineers based on written examinations, GPAs, and skills. The standard job profile is that of a technician, and the organisations that hire include BSNL, MTNL, ISRO, DRO, and ONGC, among others. Electronics engineers can also find jobs in financial services, such as banking, as technicians or junior engineers. Look for jobs in government colleges and universities where you can teach or research. After finishing this degree, you can do either an M.Tech or an MBA after your B.Tech. This will increase your chances of getting a job.

 

Top Companies Hiring Electronics Engineering Graduates in India

 

What are the other options to explore after Electronics and Communication Engineering?

 

Higher Education

 

Going for higher studies will make it easier for you to climb the success ladder. Not only will you become more qualified, but the chances of getting good jobs after they finish studying will also be high. There are many fields where students can land good jobs. They include

 

  • Nanotechnology
  • Software Engineering
  • Embedded Systems
  • Information/ Cyber Security
  • VLSI Design

Qualification Criteria

 

Students should have a bachelor's degree in electronics and communication engineering, electronics and instrumentation, or electrical engineering. They should also have scored at least 60% marks and have a valid GATE score.

 

Career Opportunities after Higher Studies in Electronics and Communication

 

Students can find job opportunities in both private and government sectors. Candidates must appear for UPSC or PSC entrance exams to secure a government job. UPSC conducts this exam annually, while other PSCs have their exams to fill job vacancies. Information about these exams is published in leading newspapers. Some potential employers for Electronics and Communications graduates include:

 

  • Atomic Energy Commission
  • Central Electronics Limited
  • Defence Sectors
  • Directorate General Posts and Telegraphs Departments
  • Hindustan Aeronautics Limited
  • Indian Railways
  • Ministry of Civil Aviation

People with a master's degree in this field can start their own businesses, like electronic stores or repair/assembly shops. Electronics is crucial in today's industry, so the profit is likely to be more than the cost. Banks and small-scale industrial development corporations are willing to provide financial assistance to those who want to kickstart their own businesses.

 

Certification Courses

 

After completing a BTech, certification programs offer an excellent opportunity to enhance skills and boost your career quickly. These programs require less time and are more cost-effective than alternative study options. A typical certification program usually ranges from nine months to 1.5 years.

 

Some of the certifications you can go for are:

 

  • VLSI certification if you want to work in the Semiconductor industry
  • Embedded training is preferable for interest in robotics
  • CCNA certifications to work in IT engineering
  • Matlab/Simulink training to work in Signal processing/telecom/control system industries

Conclusion

 

There are many Job Opportunities for Electronics and Communication Engineers in India. If you study ECE, you can choose from various careers like working with wireless communication, handling hardware, being a telecom engineer, software analyst, or even a robotics engineer. The opportunities to specialize and grow in this field are plenty. ECE graduates are ready to face the industry's challenges because they have the right skills. As technology improves, the need for skilled ECE professionals is increasing, making it a promising and exciting field for those who love innovation.

 

Top 10 3D Modelling Software For Mechanical Engineers in 2020: Cracking the Technical Interview!

The 3D modelling software tools are used for a number of projects, from simulation to manufacturing. A 3D modelling software with great visualisation options can help you get a better overview of your project. A precise overview allows you to adjust and improve your parts efficiently. It is also a good method to correct the last errors.  

There are a few software that are used consistently throughout the industry. The level of proficiency that is required with specific software packages is dependent on your role as an engineer. 

Take a look at top 10 3D modelling software for mechanical engineers: 

  1. Mathcad

Mathcad is useful to every mechanical engineer, regardless of the job function. It gives you the ability to do math within a document and allows you to add relevant images and text to explain your work. The output of Mathcad is a beautifully formatted document containing ‘hand’ calculations.

  •   Ability to write and evaluate equations
  •   Unit conversion
  •   Plotting
  •   Linear algebra - Useful for solving 3D statistics problems 
  •   Programming - Useful for numeric analysis.
  1. Computer-Aided Design (CAD) Software

Computer-Aided Design (CAD) software allows building 3D models of parts and assemblies. CAD software has a drafting component that allows you to create 2D drawings of your parts that can be manufactured. CAD tools also have direct integration into an FEA (Finite Element Analysis) package so you can iterate seamlessly between design and analysis. 

Examples of 3D CAD software: SolidWorks, Unigraphics NX, CATIA, and Autodesk Inventor.

  1. Finite Element Analysis (FEA) Software

Structural analysis can be done with Finite Element Analysis (FEA). The Finite Element Analysis software allows you to analyse stresses and deflections in complex structures.  A structure is typically modelled in a 3D CAD program, its geometry is built, a mesh is created to discretise the structure into elements, forces and constraints are applied, and the model can then be solved. From the solved model, you can interrogate stresses and deflections in the structure.

Examples: ANSYS and NASTRAN.

  1. MATLAB

MATLAB is the programming language well suited for calculations with matrices and vectors. MATLAB is used when a complex numerical analysis requires a strong programming solution. It is easy to run simulation and quickly display0= results due to MATLAB’s excellent plotting capabilities. 

  1. Python

Python is a general-purpose programming language and is an excellent alternative to MATLAB. Python is open-source (free of cost), tailored for scientific programming and hosts various functionalities that can be achieved by installing the NumPy, SciPy, Pandas, etc. Other things besides numerical analysis, such as any work related to the file system, managing a database, or building a website can also be done in Python. 

  1. AutoCAD Mechanical

 AutoCAD is a 3D program that allows you to document CAD models, reuse mechanical drawing detailing tools. It enables you to create rectangles from a ribbon, restore and isolate layer groups and much more. AutoCAD Mechanical provides a huge library of standard parts and international drafting standards support.

  1. Solid Edge

Solid Edge has a great 2D orthographic view functionality and is a perfect 3D software for complex projects. It also has powerful engineering simulation capabilities for Computer-Aided Engineering.

  1. SolidWorks

SolidWorks has a user-friendly interface and can be used for design, or to create machinery parts. 

  1. ProE

ProE (also known as PTC Creo or Creo Parametric) is a 3D CAD software providing assembly modelling, finite element analysis, NURBS surface modelling, etc. It is the best pick for rapid prototyping of mechanical parts and to produce end-use products.

  1. CATIA

Catia is used for complex and detailed designs. It is used to design, simulate, analyse, and manufacture products in a variety of industries including aerospace, automotive, consumer goods, and industrial machinery, etc. 

If you are looking at cracking design and technical interview, then you must know that it is necessary to do background research about the company in which you are applying. Every company has its own product and works on specific software. Go through the requirements of the company and the software they prefer working on before applying for a job position. 

Useful tip: If you are looking at a career in the core mechanical field, you must practice designing on at least a few mechanical engineering software.  



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