Key Features of Python for Artificial Intelligence, Machine Learning and Data Science

40+ Guided Hands-on Labs
Interactive Learning Experience
Expert Support
Reports to assess validation reports

What are the prerequisites required for the Python for Artificial Intelligence, Machine Learning and Data Science?

There is no formal prerequisite needed for taking the Python for Artificial Intelligence, Machine Learning and Data Science. But it is recommended to know

Basic understanding of Python, AI & Data Science
Familiarity with Python syntax and basic operations

What are the skills you will gain in the Python for Artificial Intelligence, Machine Learning and Data Science Course?

In the Python for Artificial Intelligence, Machine Learning, and Data Science course, you will gain the following skills:

Understanding Python fundamentals: keywords, identifiers, variables, data types, and control flow.
Proficiency in working with data structures: lists, strings, and functions (including recursive and lambda functions).
Advanced Python skills: modules, packages, file handling, and exception handling.
Data manipulation and analysis with Pandas: data frames, key operations, and the IRIS dataset.
Visualization techniques: 2D and 3D scatter plots, pair plots.
Statistical concepts: distributions (normal, uniform, Bernoulli, binomial, log-normal), standardization, KDE, Q-Q plots, and hypothesis testing.
Algorithm and complexity analysis: binary search, finding common elements, and understanding space and time complexity.