Learn everything you need to become a data scientist.

Machine learning is quickly becoming a required skill for every software developer.

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.

Reviews On Our Python Courses:

• "I know enough Python to be dangerous. Most of the ML classes are so abstract and theoretical that no learning happens. This is the first class where we use concrete examples that I can relate to and allow me to learn. Absolutely love this course!" - Mary T.

  
  

• "Yes, this is an amazing start. For someone new in python this is a very simple boot course. I am able to relate to my earlier programming experience with ease!" - Gajendran C.

  
  

• "Clear and concise information" - Paul B.

  
  

• "Easy to understand and very clear explanations. So far so good!!!" - Alejandro M.

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:

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 plaform 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 Convolutional Neural Network

Build a convolutional neural network (CNN.) Learn how to use Keras with machine learning models.

Keras is a neural-network library written in Python capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML. You'll be able to enable fast experimentation with deep neural networks with Keras.

All source code is included for each project.

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