This course aims to provide an introduction to the basic principles, techniques, and applications of Machine Learning & AI. Develop expertise in popular AI & ML technologies and problem-solving methodologies, develop the ability to independently solve business problems using AI & ML, learn to use popular AI & ML technologies like Python, Anaconda (Spyder) to develop applications, develop a verified portfolio with some projects and algorithms that will showcase the new skills acquired.
1. Python for AI (Significant Functions, Packages, and Routines)
2. Statistics & Probability (Descriptive & Inferential Stats,Probability & Conditional Prob)
3. Visualization principles and techniques
4. Value-based methods (e.g. Q-learning)
5. Policy-based methods
6. Recurrent Neural Networks (RNN)
7. Deep Learning applied to Images using CNN
8. Keras library for deep learning in Python
In addition to this, there will be 8 mini-projects spread across topics such as:
• Supervised Learning
• Unsupervised Learning
• Ensemble Techniques
• Reinforcement Learning
• Deep Learning
• A hard copy will be provided on the 2nd day of the workshop.
• CERTIFICATE OF COMPLETION.
• INTERNSHIP OPPORTUNITIES TO TOP PERFORMERS.
• Also a digital certificate that can be downloaded any time and any number of times by which you can download from login IDs provided by the company.