Becoming an Artificial Intelligence Engineer puts you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond. Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics and even customer service. The need for AI specialists exists in just about every field as companies seek to give computers the ability to think, learn and adapt.
The current and future demand is staggering. The New York Times reports a candidate shortage for certified AI Engineers, with fewer than 10,000 qualified people in the world to fill these jobs, which according to Paysa earn an average salary of $172,000 per year in the U.S for engineers with the required skills.
Course Outline:
This Artificial Intelligence course provides training in the skills required for a career in AI. You will master TensorFlow, Machine Learning, and other AI concepts, plus the programming languages needed to design intelligent agents, deep learning algorithms & advanced artificial neural networks that use predictive analytics to solve real-time decision-making problems.
By the end of this Artificial Intelligence Course, you will be able to accomplish the following:
- Design and build your own intelligent agents and apply them to create practical AI projects including games, machine learning models, logic constraint satisfaction problems, knowledge-base systems, probabilistic models, agent decision-making functions and more
- Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
- Understand and master the concepts and principles of machine learning, including its mathematical and heuristic aspects
- Implement deep learning algorithms in TensorFlow and interpret the results,
- Understand neural networks and multi-layer data abstraction, empowering you to analyze and utilize data like never before
- Comprehend and differentiate between theoretical concepts and practical aspects of machine learning,
- Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
- Learn about major applications of Artificial Intelligence across various use cases in various fields like customer service, financial services, healthcare etc
- Implement classical Artificial Intelligence techniques, such as search algorithms, minimax algorithm, neural networks, tracking, robot localization
- Ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques
- Formalise a given problem in the language/framework of different AI methods (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, etc)
- Master skills and tools used by the most innovative AI teams across the globe as you delve into specializations, and gain experience solving real-world challenges.
Live Project (s):
This Artificial Intelligence program includes real-life, industry-based projects on different domains to help you master concepts of Artificial Intelligence like Supervised Learning, Unsupervised Learning, Reinforcement Learning, Support Vector Machines, Deep Learning, TensorFlow, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks.
Who should take this AI course?
With the demand for AI in a broad range of industries, Matrix College’s AI course is well suited for a variety of roles and disciplines, including:
- Developers aspiring to be a 'Artificial Intelligence Scientist' or Machine Learning engineers
- Analytics Managers who are leading a team of analysts
- Information Architects who want to gain expertise in Artificial Intelligence algorithms
- Analytics professionals who want to work in machine learning or artificial intelligence
- Graduates pursuing Engineering / Computer Science looking to build a career in Artificial Intelligence and machine learning
- Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight
Prerequisites:
- Algebra, linear algebra
- Probability Theory
- Statistical Concepts
- Matrix mathematics
- Basic computer programming skills (Good to have)
- Python / MATLAB
- Calculus