Python and NumPy for Data Science: Mastering the Foundations

Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab

Learn everything you need to become a data scientist.

Enroll now to learn everything you need to know to get up to speed, whether you're a developer or aspiring data scientist. This is the course for you.

Your complete Python course for image recognition, data analysis, data visualization and more.

Don't miss the biggest Python course of the year. This is a once in a lifetime chance to enroll in a massive course.

Absolutely no experience necessary. Start with a complete introduction to Python that is perfect for absolute beginners and can also be used a review.

Jump into using the most popular libraries and frameworks for working with Python. You'll learn everything you need to become a data scientist. This includes:

0. Python Crash Course for Beginners

Learn Python with project based examples. Get up and running even if you have no programming experience. Superboost your career by masterig the core Python fundamentals.

1. Data Science with NumPy

Build projects with NumPy, the #1 Python library for data science providing arrays and matrices.

2. Data Analysis with Pandas

Build projects with pandas, a software library written for the Python programming language for data manipulation and analysis.

2. Data Visualization with PyPlot

Build projects with pyplot, a MATLAB-like plotting framework enabling you to create a figure, create a plotting area in a figure, plot lines in a plotting area, decorate the plot with labels and much more. Learn it all in this massive course.

3. Machine Learning Theory

Machine learning is in high demand and is quickly becoming a requirement on every software engineer's resume. Learn how to solve problems with machine learning before diving into practical examples.

4. Introduction to TensorFlow

Build projects with TensorFlow, the most popular platform enabling ML developers to build and deploy machine learning applications such as neural networks. Build your first linear regression model with TensorFlow. Learn how to build a dataset, model, train and test!

5. Build a Sentiment Analysis Model to Classify Reviews as Positive or Negative

All source code is included for each project.

If you buy one course this year, this is it. Sign up while spots are open.

What you'll learn

• Process text data
• Interpret sentiment in reviews
• Build a model to predict whether a review is positive or negative
• Implement logic
• Track data
• Customize graphs
• Implement responsiveness
• Build data structures
• Graph data with PyPlot
• Build 3D graphs with PyPlot
• Use common array functions
• Replace Python lists with NumPy arrays
• Build and use NumPy arrays
• Use Pandas series
• Use Pandas Date Ranges
• Read CSVs with Pandas
• Use Pandas DataFrames
• Get elements from a Series
• Get properties from a series
• Series operations
• Modify series
• Series comparisons and iteration
• Series operations
• And much more!

Requirements