The concept of Machine Learning is changing the concepts of working in the industry. Artificial Intelligence and Machine Learning experts are in huge demand globally and the demand is further going to increase. For example, voice assistance, Siri, automated cars, etc. all work on the foundation of Machine Learning.
How are Artificial Intelligence and Machine Learning different from each other?
Many people think that the two streams- AI and ML are the same but there is a lot of difference between Artificial Intelligence (AI) and Machine Learning (ML). Fast developments are taking place throughout the world due to advancements in technologies.
AI and ML are the two most important technologies evolving at a fast pace and soon these two technologies will become a normal part of our lives. AI and ML have made our lives easier. They are different in the way they work.
An AI engineer makes use of AI calculations to solve normal problems and make different programs while an ML engineer uses AI strategies for solving problems and making programs.
Presently, most of the top companies are looking for people who are well acquainted with both AI and ML.
Read ahead to know the ten important skills required for becoming an AI and ML engineer.
Important Skills for Artificial Intelligence and Machine Learning
Technical Skills
Important technical skills required for becoming an artificial and machine learning engineer include:
1. Knowledge of Statistics, Linear Algebra, and Calculus
It is recommended to have a basic knowledge of Vectors, Matrices, and Matrix multiplication. It is also recommended to have some knowledge of Derivatives and Integrals and their basic usage. Other important fields for excelling in the fields of AI and ML include Bayes, Standard Deviations, Mean, Hidden Markov Models, etc.
2. Knowledge of programming languages
As an AI and ML enthusiast, one should have proper knowledge of different computer languages such as Java, Python, and C++. The knowledge of these programming languages will make it easier to learn the strategies of AI and ML.
Python programming is undoubtedly the most common programming language used by every Machine Learning enthusiast.
3. Understanding the Signal Processing Techniques
To become proficient in ML, one should be able to understand Signal Processing and learn how to use strategies of Signal Processing. Advanced Signal Processing Algorithms like Wavelets, and Shearlets are important Signal Processing algorithms that are used in Time-Frequency Analysis and are necessary for solving difficult problems.
4. Neural Network Architectures
AI is useful for solving difficult problems that are not possible for humans to code. Neural systems are useful for solving a wide range of difficult problems such as image classification, speech recognition, and translation.
5. Applied Math and Algorithms
Learning calculation hypothesis is the most important requirement for becoming proficient in AI and ML. the knowledge of calculation hypotheses will help an individual to understand difficult topics such as quadratic programming, convex optimization, gradient descent, and summations.
Non-technical Skills
Important non-technical skills required for becoming an artificial and machine learning engineer include the following:
1. Communication
Proper communication is the most important skill required for any job. An AI/ML engineer should be capable of explaining the AI and ML strategies to the team members because they always work in a team. So, proper communication will help them to explain the AI and ML strategies to the non-technical people in the team such as the marketing and sales officers, architects, etc.
2. Quick Prototyping
It is an essential skill required for using the AI and ML strategies effectively. It is important to choose the right model in machine learning. Quick prototyping is useful in making different strategies that help to form a suitable structure or model.
3. Proper knowledge of industry
An AI/ML engineer should have a vast knowledge of the industry that they are working in. They should have proper information on how particular business functions and how AI and ML strategies can help any business to grow further. AI and ML skills can only help an individual if he has basic knowledge of business skills that are required for making an effective strategy for business growth. Proper knowledge of the industry will help an individual to face possible hurdles confidently and run the business successfully.
Additional Skills for AI and ML
More skills are required for becoming a machine learning engineer
1. Language, audio, and video processing
AI and ML engineers also have to work with the most important areas such as audio, text, and video. Therefore, an AI and ML engineer should have sufficient knowledge of NLTK, Gensim, and other strategies such as Sentimental Analysis, word2vec, and Summarization.
2. Physics, reinforcement learning, and computer vision
Proper learning of physics is important because we need to use machine learning techniques for different systems. Reinforcement learning is important for making improvements in AI and deep learning to a better level. This helps to use the knowledge in different fields such as self-driving cars, robotics, and other fields of AI. Computer vision along with machine learning can be used together or separately for solving very difficult systems. When two work together, they can give better results and quick output.
Why should you take up an AI/ML training course?
Becoming an AI or ML expert not only enhances your skills, knowledge, and expertise but also helps you to become eligible for getting highly paid jobs in the market. It is the need of the hour that one should upskill to move forward with the changing times.
AI and ML engineers can acquire new abilities and skills and open their career growth to a new level.
If you want to become an AI or ML engineer, you should know how to use the above-mentioned skills to start your career. To give you a heads up in your efforts of making a career in AI/ML, KnowledgeHut offers a Machine Learning with Python Course to help you acquire industry relevant training in Artificial Intelligence and Machine Learning along with a course on the very in-demand Python programming.
In conclusion
Big name companies are investing a lot of money in doing research in the field of Machine Learning and Artificial Intelligence for future projects. Therefore, for becoming an AI or ML expert, you have to improve your skills to become well acquainted with the applications of MI and AI.
You can come across new and creative AI applications once you jump into this field. Though the skills required for becoming an AI or ML engineer are difficult, it is worth spending time, money, and effort in this field as it will give you better rewards. You can make a difference in the operation of your company by acquiring AI and ML skills.