Learn Data Science with Python - Part 2: Analyze, visualize & present data

Tony Staunton, Reading, writing and teaching.

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10 Lessons (1h 19m)
    • 1. Class Introduction

      1:27
    • 2. How to get the most from this class: Skillshare 101

      1:39
    • 3. Class Frequently Asked Questions

      0:54
    • 4. How to set-up your development environment

      5:08
    • 5. Jupyter Notebook 101

      4:27
    • 6. Create Graphs, Plots and Histograms

      19:17
    • 7. Python Dictionaries

      8:23
    • 8. Python Pandas & DataFrames

      10:14
    • 9. Controlling the flow of your programs

      16:02
    • 10. Python Loops

      11:12

About This Class

In Learn Data Science with Python - Part 1: Introduction to Python you took the first step on your journey to becoming a data scientist. 

Part 2: Plots, Graphs, Dictionaries, Control Flow & Loops, is an essential step to keep moving forward. Right out of the gate you will learn Python visualizations skills that you can apply in the real world. You will learn how to master Matplotlib to produce several plots and graphs including this amazing graph:

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In lesson 2 you will learn how to create Python dictionaries which are like lists on steroids and will help you harness and manipulate massive amounts of data.

Next, you will be introduced to one of my favorite Python topics, the Pandas DataFrame which is the standard way of working with tabular data in Python. In this lesson, you will learn how to import CSV files so that you can manipulate and access the information within.

Have you ever wondered how computer programs make decisions? Well in lessons 4 & 5 you are going to find out. Boolean logic is the foundation of giving your programs the power of decision making. You will learn how to combine different comparison operators with Boolean logic to control the flow of your Python programs.

Each lesson in this class is created using Jupyter Notebooks which means that you can download the Python code, experiment and improve upon. You also get to keep the class notes for future learning and reference.

At the end, of the lesson is a final project to apply what you've learned.

After completing this class you will have the basic techniques used by real-world industry data scientists. These are topics any successful technologist absolutely needs to know. 

What are you waiting for? Enroll now and take the next step!