Do you want to make a career in AI? Here are the available options

 Do you want to make a career in AI? Here are the available options

You must have heard that the emerging Artificial Intelligence (AI) could or is taking away many jobs. If you are also worried about this, experts say that there is no need to panic. But for that, you may need new skills.

According to the World Economic Forum, about 12 million new jobs will be created due to AI in the coming days. Recently, the establishment of AI companies and the demand for AI manpower are increasing in Nepal as well. Various organizations/institutions have started using AI for their work.

In such a situation, the demand for experts in the field of AI is sure to increase. Again, this is a skill that is used internationally as well. This means that this is the most appropriate time to make a career in AI.

But how to enter AI? Today we are discussing this topic:

What is AI?

In simple terms, AI is a technology that makes work easier by using artificial intelligence. Or, the work of humans is being done by this technology. Voice assistant in Google Maps, ChatGPT, Amazon's Alexa, automatic robotic hands used in factories, driverless or autonomous cars - all these are examples of AI.

Currently, AI is in the initial stage of development. This stage helps to expand our capabilities and skills. In the future, there are even estimates that AI will have the ability to make decisions like humans.

Formal study of AI

Formal education that focuses only on AI is limited to university level, i.e. higher education. But to get admission in it, it is mandatory to study physics, chemistry and mathematics in 11th/12th. Higher education should be studied in subjects like computer science, IT and electronics.

And students studying any AI course need to know about programming. Knowledge of languages ​​like Linux command line, workflow, Java, JavaScript, C, C++, Python is also equally important.

But even if students do not know these programming languages ​​​​in the beginning, they can learn them later. Then, by gaining proficiency in any course related to AI, you can enter this field.

AI courses have already started being taught formally in Nepal. AI subjects are being taught in colleges affiliated with some foreign universities, including Kathmandu University, Purbanchal University, Lumbini Technical University.

Qualifications required for studying AI

To make a career in AI, it is necessary to have a science background. Taking the example of Kathmandu University, to get admission in the course (Bachelor's degree 'BTech in AI'), one must have taken Physics, Chemistry and Mathematics (PCA) or Physics, Mathematics and Computer Science (PMC) in class 11/12.

Similarly, one must have scored a minimum of 2.0 CGPA or more than 50 percent marks in the final examination of class 12. In addition, one must also pass the entrance exam conducted by Kathmandu University. The results of the students appearing in it also make a difference in admission. Basically, other educational institutions that teach AI have set almost the same requirements.

Bachelor's degree in AI in Nepal

In Nepal, courses such as 'B.Tech in AI', 'B.Tech in Computer Science and AI', 'BSc (Hons) Computing with Artificial Intelligence', 'BSc (Hons) Computer Science and Artificial Intelligence' are being taught.

You can study any of these courses. These are courses from local and foreign universities. You can choose the university to study based on your convenience.

AI curriculum

Mostly, AI courses include programming, computer architecture, machine learning, neural networks, robotics, big data, etc. These are similar subjects. Apart from this, there will be workshops and project work.

While studying AI at the undergraduate level, you get basic education, and after the postgraduate level, you gain expertise in a specific field.

But various courses that lead to certificates can also give your career a further boost. From time to time, renowned organizations in Nepal, such as Nami, Fuse Machine, are also providing AI-related training. Apart from the physical training, you can also take such training online.

Online courses and training

Usually, if you search Google, you will find many online courses related to AI. However, it is wise to take training from a good and reliable platform.

Stanford University's Stanford School of Engineering is offering an AI Graduate Certificate course. Under which many courses can be found, including Artificial Intelligence, Principles and Techniques, Machine Learning, Natural Language Processing with Deep Learning, Machine Learning with Graphs, Deep Learning for Computer Vision. All these courses are paid.

If Stanford University’s course seems expensive, you can also take the IBM AI Engineering course for free. It covers topics like Deep Learning, Neural Networks, Machine Learning Algorithms.

Similarly, you can also take the Microsoft AI Engineer Associate Certification course. After completing this course, students will be able to build, manage, and deploy Azure Platform and Azure Cognitive Services. AI applications.

If you want to enroll in a more advanced AI program, you can also look at a platform called Deep Learning. This platform, started by the co-founder of the online learning platform Coursera, has courses available for students of all levels. Courses from beginner to advanced levels like 'AI for Good' can be found here.

Similarly, if you use the social network LinkedIn, you must have heard of LinkedIn Learning. There, you can find courses related to AI from basic to advanced levels.

You can also study AI courses by connecting with Google AI. Google itself is a global leader in AI research. This company also publishes various research papers on AI every year. It also teaches interested and new people. Google AI's Machine Learning Crash Course is available for free. This 15-hour course can also be useful.

Required Skills

Programming

AI engineers should have good knowledge in programming languages ​​like Python, R, Java, C++.

Machine Learning and Algorithms

It is not enough for an AI engineer to have a programming language. To build an AI model, one must also have good skills in machine learning and algorithms. Along with this, strong knowledge in linear algebra, probability, statistics is also required.

Spark and Big Data

AI engineers often have to work with large amounts of data. To manage such data, one must have expertise in big data technologies like Spark, Apache Spark, Hadoop.

Algorithms and Frameworks

A deep knowledge of algorithms and frameworks is required to make machine learning models work. Large amounts of data are often in unstructured formats. To bring this into a structured format, machine learning models such as neural networks, recurrent neural networks, and generative adversarial networks (GAN) need to be used.

Non-technical skills

AI engineers need technical skills. Along with this, non-technical skills are also needed. Non-technical skills such as problem-solving skills, the ability to work in a team, time management, and critical thinking are also equally important.

Now, let's understand what to do as a career after studying these topics of AI.

Responsibilities of an AI technician

Mainly, an AI engineer works by understanding the business needs of their customers or companies and developing AI models using machine learning algorithms and deep learning neural networks.

This requires a good understanding of programming, software engineering, and data science. But not only building models, one must also be able to process data and maintain AI systems using various AI tools.

Is it difficult to become an AI technician?

At first glance, it seems challenging. But it is not that difficult. People who are weak in computer science, programming or mathematics may find it difficult. This requires training, practice and dedication. The main thing is that there are plenty of resources available to learn.

Can you make a career in AI without a degree?

The simple answer is, you can. Although having a relevant degree is good. You can make a career in it without formal education by taking online courses, bootcamps, training.

But for this, it is necessary to build a strong foundation in computer programming, data structures, and algorithms. Or, let's say, having a degree is like gold.

The future

Today, the day has come when it is not being used, rather than where it is being used. It is being used in almost every field, including designing, business, education, research and development, automobile, medical, music, sports.

The income of those who work in it is also attractive. Moreover, pursuing this field can also open doors to work opportunities in companies like Amazon, Microsoft, Google, IBM.

Specifically; After studying AI, you can become a machine learning engineer, data scientist, AI researcher, robotics engineer, big data analyst, etc. Overall, making a career in the AI ​​field means moving forward with time.