AI market trends and growth forecasts Understanding AI & its related terms ( Machine learning/ Deep Learning etc) difference between machine learning & reasoning
computer programming (rule based vs ML )approach
Basic python language/libraries fundamentals to understand ML code examples
types of machine/deep learning (hands-on code training)
supervised learningĀ
unsupervised learningĀ
reinforcement learning
ML/DL practical domains (hands-on code training)
Computer vision
Natural Language processing
Time series analysis/forecasting
supervised/unsupervised learning on structured/tabular data
speech anaylsis
Discriminative vs generative models (LLMS, ChatGPT etc)
Tools & cloud services used to implement ML/DL appsĀ