5+ Best Courses in Machine Learning, Ranked by Your Reviews

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.

5+ Best Machine Learning Courses and Specialization [2019] 

The demand for Machine Learning Engineers and Research Scientists is exploding. This compilation of Best Machine Learning Courses and Specialization is suitable for beginners, intermediate learners as well as advanced learners.

1. Introduction to Machine Learning with R

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Introduction to Machine Learning with R from DataCamp will help you in learning the true fundamentals of Machine Learning and experiment with the techniques. This course is 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.

Introduction to Machine Learning with R 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

What you will 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

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2. 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.

Machine Learning course offered by Stanford provides an in-depth introduction to Machine Learning, helps you understand statistical modeling and discusses best practices for applying Machine Learning.

Machine Learning Courses

What you will 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

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3. Understanding Machine Learning with Python

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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 Course is right for you, if you’re new to Machine Learning and have some experience in Python programming.

Understanding Machine Learning with Python course will hone your Machine Learning craft using sckit-learn, the most powerful Machine Learning library used by every Machine Learning Engineer and Data Scientist.

Machine Learning Course

What you will 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: 

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4. Become a Machine Learning Engineer  Job Guarantee

This intensive AI/machine learning course—the first with a job guarantee—will equip you to transition into a role as a machine learning engineer. The extensive curriculum was curated by machine learning experts with experience at companies like Airbnb and Intel.

While you’ll learn the advanced concepts machine learning engineers are expected to understand, you’ll also develop production engineering skills. By the end of the program, you’ll have designed a machine learning system, built a prototype, and deployed an application that can be accessed via API or web service.

Is it right for you?

AI/Machine Learning Career Track was designed for people with a background in software engineering. It’s a self-guided, mentor-led, career-focused bootcamp complete with a job guarantee. If you don’t find a job within six months of graduating, you will get a refund for your tuition.

You’ll learn to apply machine learning and deep learning algorithms through case studies and projects. You’ll have one-on-one guidance from your mentor, an experienced machine learning engineer, as you complete your coursework, build projects, and search for a job.

Machine Learning Engineer Course Source: Springboard

What you will learn?
  • Overview of AI and the machine learning engineering stack
  • Data wrangling at scale and statistics for AI
  • Supervised and unsupervised machine learning algorithms
  • Deep learning fundamentals, including neural network principles
  • Natural Language Processing (AI case study)
  • Foundations of computer vision and deep learning for images (AI case study)
  • Building and deploying large-scale AI systems (capstone project)


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5. Intro to Machine Learning

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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?

Intro to Machine Learning is a Free Course and a recommenced  prerequisite course for Machine Learning Engineer Nano degree Program offered by Udacity.

If you're a beginner in Machine Learning with some Programming experience and background in Statistics, this course will help you skill yourself 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

What you will 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 

6. Machine Learning Crash Course

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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 to  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.

Also, Google Cloud is offering 2 Specializations on Machine Learning with TensorFlow ⬅ Check

Machine Learning Courses

What you will 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 

Before You Go 

So that was our take on the Best Machine Learning Courses for 2019 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 . . .