You’ll begin by exploring the basics of Python programming and why Python is such a powerful tool for data analysis. You’ll learn about Jupyter Notebooks, an interactive environment for coding and data work. You’ll investigate how to use variables and data types to store and organize your data; and, you’ll begin practicing important coding skills.

Next, you’ll discover how to call functions to perform useful actions on your data. You’ll also learn how to write conditional statements to tell the computer how to make decisions based on your instructions. And you’ll practice writing clean code that can be easily understood and reused by other data professionals.

Here, you’ll learn how to use iterative statements, or loops, to automate repetitive tasks. You’ll also learn how to manipulate strings using slicing, indexing, and formatting. 

Now, you’ll explore fundamental data structures such as lists, tuples, dictionaries, sets, and arrays. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. 

•  Introduction to Object-Oriented Programming (OOP)
• Advantages of Object Oriented Programming
• Introduction to Object-Oriented Programming in Python

Class, Object, Inheritance, Encapsulation, Polymorphism and more.

You will put everything you have learned about Python so far into practice with an end-of-course project. You will select a business problem from a list of options and use the given data to solve the problem. This project is an opportunity to demonstrate your skills and build a professional portfolio you can use to showcase your work to potential employers.