Machine Learning is a field of computer science that provides our computers with the ability to learn without being explicitly programmed. It is at the core of many of the products and services that we use every day.

It is an exciting field. It’s what makes self-driving cars, smart speakers, and other artificial intelligence technologies possible.

Machine learning is a topic that’s been seeing a lot of interest lately. It has applications in a huge range of industries, including finance, medicine, education, and more. According to a new analysis by International Data Corp. (IDC), machine learning is one of the fastest-growing roles in technology over the next five years.

It’s a difficult topic to get to grips with, in all honesty. That's why I've decided to put together a list of the top machine learning courses on Udemy based on student reviews and instructor experience.

## 1. Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™ is an introduction to the most essential techniques in machine learning, with a focus on hands-on computer science tools. This course is aimed at people who are new to machine learning and data science and want to learn the essential concepts and techniques.

With this hands-on course, you’ll learn the basics of machine learning, explore the two most popular machine learning languages (Python and R) and get to grips with the latest techniques. It is taught by two leading data science bestselling instructors and it is also featured as the most popular machine learning course on Udemy (754,000+ students).

It assumes some programming experience (familiarity with the Python or R programming language), but no prior knowledge of machine learning.

**Course Rating** - 4.5 / 5**
Course Instructors - **Kirill Eremenko (Data Scientist) and Hadelin de Ponteves (AI Entrepreneur)

**Price -**

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## 2. Python for Data Science and Machine Learning Bootcamp

Machine learning and data science are two of the hottest topics in tech right now. In this course, you’ll learn the principles of machine learning, and demonstrate your understanding with hands-on Python exercises.

You’ll learn about the most important machine learning and data science algorithms, and gain practical experience using them to solve real-world problems.

Further along the course, you'll

- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
- Learn K-Means Clustering
- Learn Logistic Regression
- Understand Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines

**Course Rating** - 4.6 / 5**
Course Instructors - **Jose Portilla (Head of Data Science, Pierian Data Inc.)

**Price -**

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## 3. Machine Learning, Data Science and Deep Learning with Python

This all-in-one course is your one-stop guide to mastering machine learning, data science, and deep learning. Taken by 144,000+ students, this course is aimed at providing a comprehensive and hands-on guide to machine learning.

You'll learn to make predictions using linear regression, polynomial regression, and multivariate regression, build artificial neural networks with Tensorflow and Keras, classify images, data, and sentiments using deep learning,

visualize data with Matplotlib and Seaborn, understand reinforcement learning - and how to build a Pac-Man bot, classify data using various algorithms, and a lot more

Some little experience with python programming and high school maths is required.

**Course Rating** - 4.6 / 5**
Course Instructors - **Frank Kane (Founder, Sundog Education)

**Price -**

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## 4. Data Science and Machine Learning Bootcamp with R

The Data Science and Machine Learning Bootcamp with R course is a highly interactive course designed to teach you the fundamentals of data science and machine learning using the R programming language. You'll learn the tools, methods, and theory to work with large data sets and make predictions based on that data.

You don't have to know R, the course teaches you R programming from the ground up before progressing into its use for data science and machine learning. Data is becoming more and more prevalent in our lives, and data science is the hot new career field. If you want to work with data or just understand it better, this course is for you.

**Course Rating** - 4.6 / 5**
Course Instructors - **Jose Portilla (Head of Data Science, Pierian Data Inc.)

**Price -**

**Get 90% Off Now!**

## 5. Scala and Spark for Big Data and Machine Learning

Scala and Spark are two technologies that are making major waves in the world of** big data** and machine learning. The two technologies are complementary, and many data scientists and engineers have found them to be a winning combination.

If you want to learn to use Scala and Spark together for large-scale data processing, this course is for you. It starts off with an introduction to scala programming then gradually to using spark to process large datasets.

**Course Rating** - 4.6 / 5**
Course Instructors - **Jose Portilla (Head of Data Science, Pierian Data Inc.)

**Price -**

**Get 90% Off Now!**

## 6. Machine Learning Practicals: 6 Real-World Applications

As you may have already guessed, this course is aimed at getting your hands dirty by solving real industry machine learning problems with Python.

- You will know how a real data science project looks like
- You will be able to include these Case Studies in your resume
- You will be able better market yourself as a Machine Learning Practitioner
- You will feel confident during a Data Science interview
- You will learn how to chain multiple ML algorithms together to achieve the goal
- You will learn the most advanced Data Visualization techniques with Seaborn and Matplotlib
- You will learn Logistic Regression
- You will learn L1 Regularization (Lasso)
- You will learn Random Forest Classifier

**Course Rating** - 4.3 / 5**
Course Instructors - **Rony Sulca (Data Scientist at MoneyLion)

**Price -**

**Get 90% Off Now!**

## 7. Unsupervised Machine Learning Hidden Markov Models in Python

In unsupervised machine learning, there are no labels to rely on for training, so we need to find a way to do so without the help of a human. Hidden Markov models can allow us to classify observations without any labels.

In this course, you'll be implementing a Hidden Markov Model in Python from scratch, and cover how to use the HMM to classify sequences of observations. Here are a few of the stuff you'll learn:

- Understand how Markov Models work
- Write a Markov Model in code
- Apply Markov Models to any sequence of data
- Understand the mathematics behind Markov chains
- Apply Markov models to language
- Apply Markov models to website analytics
- Understand how Google's PageRank works
- Understand Hidden Markov Models
- Write a Hidden Markov Model using Theano
- Understand how gradient descent, which is normally used in deep learning, can be used for HMMs

This course is suitable for programmers who already have some experience with machine learning or data science. This course also happens to be the highest-rated (4.7 / 5) machine learning course on Udemy

**Course Rating** - 4.7 / 5**
Course Instructors - **Lazy Programmer Team (Artificial Intelligence and Machine Learning Engineer)

**Price -**

**Get 90% Off Now!**

Machine Learning is one of the hot fields with the big money right now. And for good reason: it’s the engine powering the next wave of intelligent applications and services. Machine learning is an important skill in modern-day data science. It's what allows us to turn large sets of data into actionable insights. These courses can turn you into a machine learning expert in no time.

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