An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. — Course 4 of 4
Learn about control structures, one of the most powerful parts of programming. This course covers conditionals, loops, functions, and error handling, specifically in Python bu
Get hands-on experience with the science and research aspects of data science work, from setting up a proper data study to making valid claims and inferences from data experim
Learn how to use Python and its popular libraries such as NumPy and Pandas, as well as the PyTorch Deep Learning library. You'll then apply them to build Neural Networks an
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python script
Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This Machine Learning with Python course will give you all the tool
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routin
This course is a ”no prerequisite” introduction to Python Programming. You will learn about variables, conditional execution, repeated execution and how we use functions.
The second course in Python for Everybody explores variables that contain collections of data like string, lists, dictionaries, and tuples. Learning how to store and represe
Data visualization is the graphical representation of data in order to interactively and efficiently convey insights to clients, customers, and stakeholders in general.