Learn the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis in this course for beginners. This was originally presented as a live course.

By the end of the course, you will be able to build an end-to-end real-world course project and earn a verified certificate of accomplishment. There are no prerequisites for this course.

Learn more and register for a certificate of accomplishment here: http://zerotopandas.com

This full course video includes 6 lectures (all in this video):
• Introduction to Programming with Python
• Next Steps with Python
• Numerical Computing with Numpy
• Analyzing Tabular Data with Pandas
• Visualization with Matplotlib and Seaborn
• Exploratory Data Analysis - A Case Study

💻 Code References
• First steps with Python: https://jovian.ai/aakashns/first-steps-with-python
• Variables and data types: https://jovian.ai/aakashns/python-variables-and-data-types
• Conditional statements and loops: https://jovian.ai/aakashns/python-branching-and-loops
• Functions and scope: https://jovian.ai/aakashns/python-functions-and-scope
• Working with OS & files: https://jovian.ai/aakashns/python-os-and-filesystem
• Numerical computing with Numpy: https://jovian.ai/aakashns/python-numerical-computing-with-numpy
• 100 Numpy exercises: https://jovian.ai/aakashns/100-numpy-exercises
• Analyzing tabular data with Pandas: https://jovian.ai/aakashns/python-pandas-data-analysis
• Matplotlib & Seaborn tutorial: https://jovian.ai/aakashns/python-matplotlib-data-visualization
• Data visualization cheat sheet: https://jovian.ai/aakashns/dataviz-cheatsheet
• EDA on StackOverflow Developer Survey: https://jovian.ai/aakashns/python-eda-stackoverflow-survey
• Opendatasets python package: https://github.com/JovianML/opendatasets
• EDA starter notebook: https://jovian.ai/aakashns/zerotopandas-course-project-starter

⭐️ Course Contents ⭐️
0:00:00 Course Introduction

Lecture 1

  • 0:01:42 Python Programming Fundamentals
  • 0:02:40 Course Curriculum
  • 0:05:24 Notebook - First Steps with Python and Jupyter
  • 0:08:30 Performing Arithmetic Operations with Python
  • 0:11:34 Solving Multi-step problems using variables
  • 0:20:17 Combining conditions with Logical operators
  • 0:22:22 Adding text using Markdown
  • 0:23:50 Saving and Uploading to Jovian
  • 0:26:38 Variables and Datatypes in Python
  • 0:31:28 Built-in Data types in Python
  • 1:07:19 Further Reading

Lecture 2

  • 1:08:46 Branching Loops and Functions
  • 1:09:02 Notebook - Branching using conditional statements and loops in Python
  • 1:09:24 Branching with if, else, elif
  • 1:15:25 Non Boolean conditions
  • 1:19:00 Iteration with while loops
  • 1:28:57 Iteration with for loops
  • 1:36:27 Functions and scope in Python
  • 1:36:53 Creating and using functions
  • 1:42:24 Writing great functions in Python
  • 1:45:38 Local variables and scope
  • 2:08:19 Documentation functions using Docstrings
  • 2:11:40 Exercise - Data Analysis for Vacation Planning

Lecture 3

  • 2:17:17 Numercial Computing with Numpy
  • 2:18:00 Notebook - Numerical Computing with Numpy
  • 2:26:09 From Python Lists to Numpy Arrays
  • 2:29:09 Operating on Numpy Arrays
  • 2:34:33 Multidimensional Numpy Arrays
  • 3:03:41 Array Indexing and Slicing
  • 3:17:49 Exercises and Further Reading
  • 3:20:50 Assignment 2 - Numpy Array Operations
  • 3:29:16 100 Numpy Exercises
  • 3:31:25 Reading from and Writing to Files using Python

Lecture 4

  • 4:02:59 Analysing Tabular Data with Pandas
  • 4:03:58 Notebook - Analyzing Tabular Data with Pandas
  • 4:16:33 Retrieving Data from a Data Frame
  • 4:32:00 Analyzing Data from Data Frames
  • 4:36:27 Querying and Sorting Rows
  • 5:01:45 Grouping and Aggregation
  • 5:11:26 Merging Data from Multiple Sources
  • 5:26:00 Basic Plotting with Pandas
  • 5:38:27 Assignment 3 - Pandas Practice

Lecture 5

  • 5:52:48 Visualization with Matplotlib and Seaborn
  • 5:54:04 Notebook - Data Visualization with Matplotlib and Seaborn
  • 6:06:43 Line Charts
  • 6:11:27 Improving Default Styles with Seaborn
  • 6:16:51 Scatter Plots
  • 6:28:14 Histogram
  • 6:38:47 Bar Chart
  • 6:50:00 Heatmap
  • 6:57:08 Displaying Images with Matplotlib
  • 7:03:37 Plotting multiple charts in a grid
  • 7:15:42 References and further reading
  • 7:20:17 Course Project - Exploratory Data Analysis

Lecture 6

  • 7:49:56 Exploratory Data Analysis - A Case Study
  • 7:50:55 Notebook - Exploratory Data Analysis - A case Study
  • 8:04:36 Data Preparation and Cleaning
  • 8:19:37 Exploratory Analysis and Visualization
  • 8:54:02 Asking and Answering Questions
  • 9:22:57 Inferences and Conclusions
  • 9:25:00 References and Future Work
  • 9:29:41 Setting up and running Locally
  • 9:34:21 Project Guidelines
  • 9:45:00 Course Recap
  • 9:48:01 What to do next?
  • 9:49:10 Certificate of Accomplishment
  • 9:50:11 What to do after this course?
  • 9:52:16 Jovian Platform

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Data Analysis with Python Course - Numpy, Pandas, Data Visualization
10.45 GEEK