Machine Learning & Data Science Certification Training Bundle

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8 Courses & 48.5 Hours
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What's Included

Tensorflow and Keras Masterclass For Machine Learning and AI in Python
  • Experience level required: Beginner
  • Access 62 lectures & 5 hours of content 24/7
  • Length of time users can access this course: Lifetime

Course Curriculum

62 Lessons (5h)

  • Introduction to the Course
    Tensorflow and Keras For Data Science2:12
    Data and Code
    Python Data Science Environment
    For Mac Users
    Install Tensorflow15:12
    Written Instructions for Tensorflow Install
    Install Keras on Windows 105:16
    Install Keras with Mac4:19
    Written Keras Installation Instructions
  • Introduction to Python Data Science Packages
    Python Packages For Data Science3:16
    Introduction to Numpy3:46
    Create Numpy10:51
    Numpy for Statistical Operations7:23
    Introduction to Pandas12:06
    Read in CSV7:13
    Read in Excel5:31
    Basic Data Cleaning4:30
  • Introduction to Tensorflow
    A Brief Touchdown2:36
    A Brief Touchdown: Computational Graphs2:56
    Common Mathematical Operator
    A Tensorflow Session4:37
    Interactive Tensorflow Session1:38
    Constants and Variables in Tensorflow3:42
    Placeholders in Tensorflow
  • Introduction to Keras
    What is Keras?3:29
  • Some Preliminary Tensorflow and Keras Applications
    Theory of Linear Regression (OLS)10:44
    OLS From First Principles9:22
    Visualize the Results of OLS3:28
    Multiple Regression With Tensorflow-Part 15:08
    Estimate With Tensorflow Estimators3:05
    Multiple Regression With Tensorflow Estimators5:24
    More on Linear Regressor Estimator8:24
    GLM: Generalized Linear Model5:25
    Linear Classifier For Binary Classification9:33
    Accuracy Assessment For Binary Classification4:19
    Linear Classification with Binary Classification With Mixed Predictors8:15
    Softmax Classification With Tensorflow7:35
  • Some Basic Concepts
    What is Machine Learning?
    Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)9:17
  • Unsupervised Learning With Tensorflow and Keras
    What is Unsupervised Learning?5:32
    Autoencoders for Unsupervised Classification1:46
    Autoencoders in Tensorflow (Binary Class Problem)7:32
    Autoencoders in Tensorflow (Multiple Classes)5:43
    Autoencoders in Keras (Simple)5:43
    Autoencoders in Keras (Sparsity Constraints)4:32
  • Neural Network for Tensorflow & Keras
    Multi Layer Perceptron (MLP) with Tensorflow6:24
    Multi Layer Perceptron (MLP) With Keras3:31
    Keras MLP For Binary Classification4:01
    Keras MLP for Multiclass Classification6:01
    Keras MLP for Regression3:27
  • Deep Learning For Tensorflow & Keras
    Deep Neural Network (DNN) Classifier With Tensorflow6:47
    Deep Neural Network (DNN) Classifier With Mixed Predictors8:11
    Deep Neural Network (DNN) Regression With Tensorflow5:24
    New Lecture
    Wide & Deep Learning (Tensorflow)11:34
    DNN Classifier With Keras3:30
    DNN Classifier With Keras-Example 24:23
  • Autoencoders with Convolution Neural Networks (CNN)
    Autoencoders With CNN-Tensorflow7:15
    Autoencoders With CNN- Keras4:46
  • Recurrent Neural Network (RNN)
    Introduction to RNN5:40
    LSTM for Time Series6:24
    LSTM for Stock Prices7:21

Tensorflow and Keras Masterclass For Machine Learning and AI in Python

Minerva Singh


Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a Data Scientist on the side. As a part of her research, she has to carry out extensive data analysis, including spatial data analysis using tools like R, QGIS, and Python. Minerva also holds an MPhil degree in Geography and Environment from Oxford University.


This course is your complete guide to practical machine and deep learning using the Tensorflow and Keras frameworks in Python. In the age of Big Data, companies across the globe use Python to sift through the avalanche of information at their disposal and the advent of Tensorflow and Keras is revolutionizing deep learning. This course will help you break into this booming field.

  • Access 62 lectures & 5 hours of content 24/7
  • Get a full introduction to Python Data Science
  • Get started w/ Jupyter notebooks for implementing data science techniques in Python
  • Learn about Tensorflow & Keras installation
  • Understand the workings of Pandas & Numpy
  • Cover the basics of the Tensorflow syntax & graphing environment and Keras syntax
  • Discover how to create artificial neural networks & deep learning structures w/ Tensorflow & Keras


Important Details

  • Length of time users can access this course: lifetime
  • Access options: web streaming, mobile streaming
  • Certification of completion included
  • Redemption deadline: redeem your code within 30 days of purchase
  • Experience level required: beginner


  • Internet required


  • Unredeemed licenses can be returned for store credit within 30 days of purchase. Once your license is redeemed, all sales are final.