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Course Outline
Introduction
Overview of Artificial Intelligence (AI)
- Machine learning
- Computational intelligence
Understanding the Concepts of Neural Networks
- Generative networks
- Deep neural networks
- Convolution neural networks
Understanding Various Learning Methods
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Semi-supervised learning
Other Computational Intelligence Algorithms
- Fuzzy systems
- Evolutionary algorithms
Exploring Artificial Intelligence Approaches to Optimization
- Choosing AI Approaches Effectively
Learning about Stochastic Dynamic Programming
- Relationship with AI
Implementing Mechatronic Applications with AI
- Medicine
- Rescue
- Defense
- Industry-agnostic trend
Case Study: The Intelligent Robotic Car
Programming the Major Systems of a Robot
- Planning the Project
Implementing AI Capabilities
- Searching and Motion Control
- Localization and Mapping
- Tracking and Controlling
Summary and Next Steps
Requirements
- Basic understanding of computer science and engineering
Audience
- Engineers
Testimonials
Abhi always made sure we were following along. Good mix of practice and theory.
Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Deep Reinforcement Learning with Python Course
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Artificial Neural Networks, Machine Learning, Deep Thinking Course
Really simple, easy to follow explanations Covered everything necessary in enough detail to understand fully, but so that it was not overwhelming good mix of theory and practice
Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Introduction to the use of neural networks Course
Working with real industry-leading ML tools, real datasets and being able to consult with a very experienced data scientist.
Zakład Usługowy Hakoman Andrzej Cybulski
Applied AI from Scratch in Python Course
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
Jimena Esquivel - Zakład Usługowy Hakoman Andrzej Cybulski
Applied AI from Scratch in Python Course
The trainer was a professional in the subject field and related theory with application excellently
Fahad Malalla - Tatweer Petroleum
Applied AI from Scratch in Python Course
The informal exchanges we had during the lectures really helped me deepen my understanding of the subject
- Explore
Deep Reinforcement Learning with Python Course
Graphs in R :)))
Faculty of Economics and Business Zagreb
Neural Network in R Course
We gained some knowledge about NN in general, and what was the most interesting for me were the new types of NN that are popular nowadays.
Tea Poklepovic
Neural Network in R Course
new insights in deep machine learning
Josip Arneric
Neural Network in R Course
the interactive part, tailored to our specific needs
Thomas Stocker
Introduction to the use of neural networks Course
Ann created a great environment to ask questions and learn. We had a lot of fun and also learned a lot at the same time.
Gudrun Bickelq
Introduction to the use of neural networks Course
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.
Jonathan Blease
Artificial Neural Networks, Machine Learning, Deep Thinking Course
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