Artificial intelligence (AI) is a broad term covering the multidisciplinary science of analysing and building human-like intelligence into machines so that they “think” and act rationally.
The discipline integrates computer science and logic with cognitive psychology and – depending on the field involved – draws on biology, natural language and philosophy to translate the underlying principles of human cognitive processes into programming that triggers specific action in a computer, leading to machine and other action.
Who is it for?
Anyone who is preparing to work with AI.
Certificates are awarded on the following basis:
- Certificate of completion: Cumulative average of 80% in online tests
- Certificate of participation: Cumulative average of 50%-79% for online tests
- Certificate of attendance: Cumulative average of less than 50% for online tests
You should emerge from this course:
- Familiar with the evolution of AI;
- Understanding the major components of artificial intelligence, including how to represent knowledge and reasoning in programming;
- Understanding how neural networks and machine learning work;
- Familiar with data preparation requirements;
And able to:
- Structure – and know when to use – different types of search;
- Structure Bayesian, clustering, decision-tree and instance-based algorithms;
- Deal with constraints;
- Apply basic AI concepts to solve problems in game writing, and to implement search techniques; and
- Write a basic AI app.
You will cover
Why it is important to be able to discuss AI; commonly used terminology; how AI works; how and when it can be applied; use cases; strategic application of AI; finding the right problem to solve; designing and implementing an AI solution; common pitfalls; managing regulations; the future of AI.
- Basic computer knowledge
- Data structure knowledge will give you an advantage, but is not compulsory
- To complete the final task in this course you must be familiar with a coding language such as Python or R
- Junior AI professional