The 5 Best Machine Learning Courses, Ranked by Your Reviews

The demand for Machine Learning Engineers and Research Scientists is exploding. A team of 5 Machine Learning Enthusiasts and 4 Content Researchers have put a tremendous amount of efforts to come up with this compilation of Best Machine Learning Tutorial, Course and Specialization which a motivated individual could use as a springboard for a rewarding and lucrative career in the field of Machine Learning.

Best Machine Learning Courses and Specialization [2018] 

This compilation of Best Machine Learning Courses and Specialization is suitable for beginners, intermediate learners as well as advanced learners.


1. Machine Learning Offered by Stanford

Stanford UniversityThis is one of the best and highly recommended courses on Machine Learning across the internet. Created by Artificial Intelligence Pioneer - Andrew Ng, Co-Founder of Coursera, Landing AI and Adjunct Professor at Stanford University.

In this course, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Is it right for you?

This course is the perfect place for beginners to understand the core idea of teaching a computer to learn concepts using data without being explicitly programmed. This course provides an in-depth introduction to Machine Learning, helps you understand statistical modeling and discusses best practices for applying Machine Learning.

Machine Learning Courses
Image Source: coursera.org
What you'll learn:
  • Introduction to Machine Learning, Linear Regression with One Variable, Linear Algebra Review
  • Learn Linear Regression with Multiple Variables and Octave/Matlab Tutorial
  • Understand Logistic Regression and Regularization
  • Learn the core concepts of Neural Networks Representation and Learning
  • Advice for Applying Machine Learning, Machine Learning System Design
  • Understand Support Vector Machines.
  • Learn Unsupervised Learning and Dimensionality Reduction
  • Explore Anomaly Detection and Recommender Systems
  • Large Scale Machine Learning and Application Example of Photo OCR

User Rating: Rated 4.9 out of 5 of 81,708 ratings

Certificate: Yes

Go to Course 

2. Introduction to Machine Learning with R

DataCamp Logo

This course from DataCamp will help you in learning the true fundamentals of Machine Learning and experiment with the techniques. Created by Vincent Vankrunkelsven, A DataCamp Instructor with Masters in AI and Gilles Inghelbrecht, A Doctoral Student with Degree in Fundamental Mathematics and a solid background in Classical Statistics.

This course will help you gain a firm understanding in training of different machine learning models and learn three of the most basic machine learning tasks: classification, regression, and clustering.

Is it right for you?

DataCamp is a time flexible, online Data Science learning platform offering tutorials and courses in Data Science, Machine Learning AI and more. This course is for anyone with a solid basis in Statistics and R Programming. By the end of this course, you'll have a basic understanding of all the main principles.

Machine Learning Courses
Image Source: DataCamp.com
What you'll learn?
  • Provides an in-depth introduction to Machine Learning fundamentals and techniques.
  • Performance Measures with Supervised and Unsupervised, Concepts of bias and variance.
  • You will Perform Classification, Build a decision tree and classify unseen observations.
  • Learn Regression and explore Predictive capabilities, the performance of regression algorithms and more.
  • Understand Clustering with Unsupervised learning techniques, k-means clustering, and hierarchical clustering.

Recommended Preparation: 

Certificate: Yes

You can Sign up here

3. Understanding Machine Learning with Python

Pluralsight Logo

This course on Machine Learning with Python will equip you to understand the concepts of using data to predict future events. This course is Created by Jerry Kurata, Technology Expert and best selling author of Machine Learning and Deep Learning Courses on Pluralsight and Coursera.

In this Course, you will learn to build predictive models and use Python to perform Supervised learning with scikit-learn.

Is it right for you?

This Machine Learning Tutorial is right for you if you’re new to Machine Learning and have some Python programming experience. This course will hone your Machine Learning craft in sckit-learn, the most powerful ML library used by every Machine Learning Engineer and Data Scientist.

Machine Learning Courses
Image Source: Pluralsight.com
What you'll learn?
  • Introduction and types of Machine Learning, Python for ML and Jupiter Notebook Demo.
  • Learn Machine Learning Working Overview and Questions to Solution Statement.
  • Learn Data Preparations and use of Github Repository.
  • Learn techniques of Loading, Cleaning, Inspecting Data, and Molding Data
  • Understand Role of the Algorithm, Narrowing the Selection, Selecting Initial Algorithm.
  • Introduction to Training Model, Training Process,  Python Training Tools, Splitting Data and Training the Algorithm.
  • Learn Testing Accuracy for Evaluating Naive Bayes Model, Performance Improvement, Fixing Unbalanced Classes, Implementing and Evaluating Cross-Validation.

User Rating: Rated 4.9 out of 5 of 382 ratings

Recommended Preparation: 

Go to Course 

4. Machine Learning Crash Course

Google Developer Logo

Machine Learning crash course from Google will introduce you to Google's best practices in machine learning to help you get ahead in the field of machine learning. Created by Peter Norvig, Computer Scientist and Director of Research at Google INC. You will Learn and apply fundamental machine learning concepts, gain real-world experience with the companion Kaggle competition, and you can also Learn with Google AI to explore the full library of Machine Learning training resources to become a practitioner of the art.

Is it right for you?

This course will help you recognize the practical benefits of mastering machine learning and understand the philosophy behind machine learning. This course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises. You will Learn best practices from Google experts on key machine learning concepts.

Machine Learning Courses
Image Source: developers.google.com
What you'll learn?
  • Learn ML Concepts of Framing, Descending to ML, Reducing Loss, TensorFlow, Generalization, Training and Test Sets, Validation, Representation, Feature Crosses, Regularization: Simplicity, Logistic Regression, Classification, Regularization: Sparsity, Neural Sets, Training Neural Sets, Multi-Class Neural Nets, Embedding.
  • Understand Machine Learning Engineering for Production Systems, Static vs Dynamic Training, Static vs Dynamic Inference, Data Dependencies.
  • Practice Machine Learning to Prediction Cancer, Analyze 18 Century Literature and Explore Real World Guideline.

Recommended Preparation: 

You can Sign up here 

5. Intro to Machine Learning

Udacity Logo

This course on Machine learning is a part of Udacity’s Machine Learning Engineer NanoDegree. Created by Sebastian Thrun, Co-Founder of Udacity and Adjunct Professor at Stanford University, along with Katie Malone, Director of Data Science Research & Development at Civic Analytics.

In this course, you’ll start with Machine learning algorithms, analyzing and training data sets. And learn the end-to-end process of investigating data through machine learning lens.

Is it right for you?

If you're a machine learning beginner, this course will help you skill you in machine learning. Hands-on exercises and projects are central to the syllabus, so if you prefer hands-on learning, you’ll definitely love this course.

Machine Learning Courses
Image Source: Udacity.com
What you'll learn?
  • Principles of Machine Learning
  • Data Investigation
  • Extraction and Representation
  • Machine Learning Algorithms
  • Performance Evaluation of ML Algorithms

Recommended Preparation: 

You can  Sign up here 

Before You Go 

So that was our take on the Best Machine Learning Courses and Specialization for 2018 which we hope puts you in the fast lane and help you get ahead in the field of Machine Learning. You may also be interested in reading Data Science with Python Track or R for Data Science.

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Wishing you the best with your career!

happy learning . . .👇🏾


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