Description

Buff your skills to keep your job and get a raise in ANY economic climate. This course BUNDLE keeps your skills sharp and your paycheque up! ● Load, clean and encode data ● Data engineering for machine learning ● Build regression and discretizer models ● Data transformation and feature selection for ridge regression

This masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.

Frequently Asked Questions How do I obtain a certificate? Each certificate in this bundle is only awarded after you have completed every lecture of the course.

Many of our students post their Mammoth Interactive certifications on LinkedIn. Not only that, but you will have projects to show employers on top of the certification.

Is this an eBook or videos? The majority of this course bundle will be video tutorials (screencasts of practical coding projects step by step.) We will also have several PDFs and all source code.

Can’t I just learn via Google or YouTube? This bundle is much more streamlined and efficient than learning via Google or YouTube. We have curated a massive 5 - course curriculum to take you from absolute beginner to starting a high - paying career.

How will I practice to ensure I’m learning? With each section there will be a project, so if you can build the project along with us you are succeeding. There is also a challenge at the end of each section that you can take on to add more features to the project and advance the project in your own time.

Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more. Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you.

Try a course today.

• 1. 00 - Mammoth Interactive Courses Introduction
  • Data Engineering and Machine Learning Masterclass | About Mammoth Interactive | 0.0

    1:11

  • Data Engineering and Machine Learning Masterclass | How to Learn Online Effectively | 0.1

    13:45

• 2. 00 - Python Introduction
  • Data Engineering and Machine Learning Masterclass | What is Python | 0.0B

    4:49

  • Data Engineering and Machine Learning Masterclass | Intro to Python | 0.1B

    4:37

• 3. 00b - Course Overview
  • Data Engineering and Machine Learning Masterclass | Course Overview | 0.0C

    3:26

• 4. 1 - (Prerequisite) Introduction to Machine Learning
  • Data Engineering and Machine Learning Masterclass | What is Machine Learning | 1.0A

    5:26

  • Data Engineering and Machine Learning Masterclass | Types of Machine Learning Models | 1.0B

    12:18

  • Data Engineering and Machine Learning Masterclass | What is Supervised Learning | 1.0C

    11:03

  • Data Engineering and Machine Learning Masterclass | How Does a Machine Learning Agent Learn | 1.1

    7:39

  • Data Engineering and Machine Learning Masterclass | What is Inductive Learning | 1.2

    4:12

  • Data Engineering and Machine Learning Masterclass | Performance of a Machine Learning Algorithm | 1.3

    4:15

  • Data Engineering and Machine Learning Masterclass | Handle Noise In Data | 1.4

    5:22

  • Data Engineering and Machine Learning Masterclass | Powerful Tools with Machine Learning Libraries | 1.5

    12:11

• 5. 2 - (Prerequisite) Introduction to Python
  • Data Engineering and Machine Learning Masterclass | Intro | 2.0.0

    4:42

  • Data Engineering and Machine Learning Masterclass | What is Google Colab | 2.0.1

    4:25

  • Data Engineering and Machine Learning Masterclass | What If I Get Errors | 2.0.2

    2:40

  • Data Engineering and Machine Learning Masterclass | How Do I Terminate A Session | 2.0.3

    2:40

  • Data Engineering and Machine Learning Masterclass | Variables | 2.3.2

    19:18

  • Data Engineering and Machine Learning Masterclass | Type Conversion Examples | 2.3.3

    10:04

  • Data Engineering and Machine Learning Masterclass | Operators | 2.3.4

    7:04

  • Data Engineering and Machine Learning Masterclass | Operators Examples | 2.3.5

    21:53

  • Data Engineering and Machine Learning Masterclass | Collections | 2.3.6

    8:23

  • Data Engineering and Machine Learning Masterclass | Lists | 2.3.7

    11:38

  • Data Engineering and Machine Learning Masterclass | Multidimensional List Examples | 2.3.8

    8:05

  • Data Engineering and Machine Learning Masterclass | Tuples Examples | 2.3.9

    8:35

  • Data Engineering and Machine Learning Masterclass | Dictionaries Examples | 2.3.10

    14:24

  • Data Engineering and Machine Learning Masterclass | Ranges Examples | 2.3.11

    8:30

  • Data Engineering and Machine Learning Masterclass | Conditionals | 2.3.12

    6:41

  • Data Engineering and Machine Learning Masterclass | If Statement Examples | 2.3.13

    10:16

  • Data Engineering and Machine Learning Masterclass | If Statement Variants Examples | 2.3.14

    11:19

  • Data Engineering and Machine Learning Masterclass | Loops | 2.3.15

    7:00

  • Data Engineering and Machine Learning Masterclass | While Loops Examples | 2.3.16

    11:30

  • Data Engineering and Machine Learning Masterclass | For Loops Examples | 2.3.17

    11:18

  • Data Engineering and Machine Learning Masterclass | Functions | 2.3.18

    7:48

  • Data Engineering and Machine Learning Masterclass | Functions Examples | 2.3.19

    9:17

  • Data Engineering and Machine Learning Masterclass | Parameters and Return Values Examples | 2.2.20

    13:46

  • Data Engineering and Machine Learning Masterclass | Classes and Objects | 2.2.21

    11:13

  • Data Engineering and Machine Learning Masterclass | Classes Example | 2.2.22

    13:11

  • Data Engineering and Machine Learning Masterclass | Object Examples | 2.2.23

    9:55

  • Data Engineering and Machine Learning Masterclass | Inheritance Examples | 2.2.24

    17:26

  • Data Engineering and Machine Learning Masterclass | Static Members Example | 2.2.25

    11:03

  • Data Engineering and Machine Learning Masterclass | Summary and Outro | 2.2.26

    4:07

• 7. 4 - Data Engineering for Machine Learning
  • Data Engineering and Machine Learning Masterclass | Scale and Encode Data With Scikit-Learn | 4.4

    3:48

  • Data Engineering and Machine Learning Masterclass | What is Scaling Data | 4.4B

    6:37

  • Data Engineering and Machine Learning Masterclass | Build, Train and Test a Machine Learning Model | 4.5

    4:37

• 8. 5 - Build Regression and Discretizer Models
  • Data Engineering and Machine Learning Masterclass | Compare Decision Tree and Linear Regression Models | 5.1

    6:27

  • Data Engineering and Machine Learning Masterclass | What is the Kbins Discretizer | 5.1C

    4:55

  • Data Engineering and Machine Learning Masterclass | Bin Data With Kbins Discretizer | 5.2

    3:42

  • Data Engineering and Machine Learning Masterclass | Compare Pinned Regression Models | 5.3

    3:39

  • Data Engineering and Machine Learning Masterclass | What is K Means Clustering | 5.5A

    11:58

  • Data Engineering and Machine Learning Masterclass | Build a Linear Regression Model on Stacked Data | 5.4

    3:20

• 9. 6 - Data Transformation and Feature Selection for Ridge Regression
  • Data Engineering and Machine Learning Masterclass | Build Univariate Nonlinear Transformation | 6.1

    1:56

  • Data Engineering and Machine Learning Masterclass | What is Gaussian Probability Distribution | 5.1B

    2:32

  • Data Engineering and Machine Learning Masterclass | What is Poisson Distribution | 5.1C

    1:09

  • Data Engineering and Machine Learning Masterclass | Build X and Y Data with Poisson Distribution in Numpy | 6.2

    3:34

  • Data Engineering and Machine Learning Masterclass | What is Logarithmic Data Transformation | 6.2C

    2:34

  • Data Engineering and Machine Learning Masterclass | Build a Ridge Regression Model | 6.3

    3:41