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Top Machine Learning Courses
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These are the top 67 Machine Learning courses and offerings found from analyzing all discussions on Reddit that mention any Coursera course.

#1
Machine Learning
Machine learning is the science of getting computers to act without being explicitly programmed.
Stanford University
Andrew Ng
13 reddit posts
1193 mentions
#2
Deep Learning Specialization
If you want to break into AI, this Specialization will help you do so.
deeplearning.ai
Andrew Ng
15 reddit posts
248 mentions
#3
Mathematics for Machine Learning Specialization
For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to h...
Imperial College London
David Dye
2 reddit posts
97 mentions
#4
TensorFlow in Practice Specialization
Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.
deeplearning.ai
Laurence Moroney
4 reddit posts
38 mentions
#5
Advanced Machine Learning Specialization
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods.
National Research University Higher School of Economics
Evgeny Sokolov
4 reddit posts
61 mentions
#6
Machine Learning Specialization
This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning.
University of Washington
Emily Fox
5 reddit posts
135 mentions
#7
Probabilistic Graphical Models Specialization
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.
Stanford University
Daphne Koller
3 reddit posts
40 mentions
#8
Neural Networks and Deep Learning
If you want to break into cutting-edge AI, this course will help you do so.
deeplearning.ai
Andrew Ng
2 reddit posts
31 mentions
#9
Data Mining Specialization
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text.
University of Illinois at Urbana-Champaign
John C. Hart
0 reddit posts
45 mentions
#10
Computational Neuroscience
This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function.
University of Washington
Rajesh P. N. Rao
0 reddit posts
29 mentions
#11
Reinforcement Learning Specialization
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).
University of Alberta
Martha White
2 reddit posts
13 mentions
#12
Probabilistic Graphical Models 1
Representation
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.
Stanford University
Daphne Koller
2 reddit posts
22 mentions
#13
Mathematics for Machine Learning
Linear Algebra
In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices.
Imperial College London
David Dye
0 reddit posts
19 mentions
#14
Convolutional Neural Networks
This course will teach you how to build convolutional neural networks and apply it to image data.
deeplearning.ai
Andrew Ng
4 reddit posts
17 mentions
#15
Sequence Models
This course will teach you how to build models for natural language, audio, and other sequence data.
deeplearning.ai
Andrew Ng
3 reddit posts
9 mentions
#16
Data Engineering, Big Data, and Machine Learning on GCP Specialization
This online specialization provides participants a hands-on introduction to designing and building data pipelines on Google Cloud Platform.
Google Cloud
Google Cloud Training
2 reddit posts
16 mentions
#17
Machine Learning with TensorFlow on Google Cloud Platform Specialization
What is machine learning, and what kinds of problems can it solve? What are the five phases of converting a candidate use case to be driven by machine learning, and why is it important that the phases not be skipped? Why are neural networks so popular now? How can you set up a supervised learning pr...
Google Cloud
Google Cloud Training
1 reddit posts
11 mentions
#18
Practical Machine Learning
One of the most common tasks performed by data scientists and data analysts are prediction and machine learning.
Johns Hopkins University
Jeff Leek, PhD
0 reddit posts
16 mentions
#19
Machine Learning Foundations
A Case Study Approach
Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems?...
University of Washington
Emily Fox
1 reddit posts
19 mentions
#20
Recommender Systems Specialization
A Recommender System is a process that seeks to predict user preferences.
University of Minnesota
Joseph A Konstan
0 reddit posts
14 mentions
#21
Machine Learning
Regression
Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,.
University of Washington
Emily Fox
0 reddit posts
14 mentions
#22
Machine Learning
Classification
Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,.
University of Washington
Emily Fox
0 reddit posts
13 mentions
#23
Natural Language Processing
This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few.
National Research University Higher School of Economics
Anna Potapenko
0 reddit posts
9 mentions
#24
IBM Applied AI Professional Certificate
Artificial Intelligence (AI) is transforming our world.
IBM
Rav Ahuja
8 reddit posts
10 mentions
#25
Machine Learning and Reinforcement Learning in Finance Specialization
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance.
New York University
Igor Halperin
0 reddit posts
9 mentions
#26
IBM AI Engineering Professional Certificate
The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence.
IBM
SAEED AGHABOZORGI
0 reddit posts
11 mentions
#27
Bayesian Methods for Machine Learning
People apply Bayesian methods in many areas: from game development to drug discovery.
National Research University Higher School of Economics
Daniil Polykovskiy
0 reddit posts
8 mentions
#28
Practical Reinforcement Learning
Welcome to the Reinforcement Learning course.
National Research University Higher School of Economics
Pavel Shvechikov
1 reddit posts
6 mentions
#29
The Unix Workbench
Unix forms a foundation that is often very helpful for accomplishing other goals you might have for you and your computer, whether that goal is running a business, writing a book, curing disease, or creating the next great app.
Johns Hopkins University
Sean Kross
0 reddit posts
7 mentions
#30
Machine Learning for Data Analysis
Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal.
Wesleyan University
Jen Rose
0 reddit posts
8 mentions
#31
Improving Deep Neural Networks
Hyperparameter tuning, Regularization and Optimization
This course will teach you the "magic" of getting deep learning to work well.
deeplearning.ai
Andrew Ng
0 reddit posts
5 mentions
#32
Introduction to Deep Learning
The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding.
National Research University Higher School of Economics
Evgeny Sokolov
0 reddit posts
5 mentions
#33
Machine Learning With Big Data
Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data.
University of California San Diego
Mai Nguyen
0 reddit posts
3 mentions
#34
Nearest Neighbor Collaborative Filtering
In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques.
University of Minnesota
Joseph A Konstan
0 reddit posts
2 mentions
#35
Introduction to Recommender Systems
Non-Personalized and Content-Based
This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic ste...
University of Minnesota
Joseph A Konstan
0 reddit posts
2 mentions
#36
Введение в машинное обучение
Не так давно получил распространение термин «большие данные», обозначивший новую прикладную область — поиск способов автоматического быстрого анализа огромных объёмов разнородной информации.
National Research University Higher School of Economics
Константин Вячеславович Воронцов
0 reddit posts
1 mentions
#37
Probabilistic Graphical Models 3
Learning
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.
Stanford University
Daphne Koller
0 reddit posts
1 mentions
#38
Probabilistic Graphical Models 2
Inference
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other.
Stanford University
Daphne Koller
0 reddit posts
1 mentions
#39
Recommender Systems
Evaluation and Metrics
In this course you will learn how to evaluate recommender systems.
University of Minnesota
Michael D. Ekstrand
0 reddit posts
1 mentions
#40
Machine Learning with Python
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python.
IBM
SAEED AGHABOZORGI
0 reddit posts
5 mentions
#41
Advanced Data Science with IBM Specialization
As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning.
IBM
Romeo Kienzler
6 reddit posts
27 mentions
#42
Applied AI with DeepLearning
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ.
IBM
Romeo Kienzler
6 reddit posts
22 mentions
#43
Reinforcement Learning in Finance
This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management.
New York University
Igor Halperin
0 reddit posts
2 mentions
#44
Fundamentals of Machine Learning in Finance
The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be mo...
New York University
Igor Halperin
0 reddit posts
1 mentions
#45
Convolutional Neural Networks in TensorFlow
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them.
deeplearning.ai
Laurence Moroney
2 reddit posts
1 mentions
#46
Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization
This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs.
Google Cloud
Google Cloud Training
0 reddit posts
6 mentions
#47
Sequence Models for Time Series and Natural Language Processing
This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.
Google Cloud
Google Cloud Training
0 reddit posts
1 mentions
#48
Google Cloud Platform Big Data and Machine Learning Fundamentals
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP).
Google Cloud
Google Cloud Training
0 reddit posts
3 mentions
#49
Sequences, Time Series and Prediction
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them.
deeplearning.ai
Laurence Moroney
0 reddit posts
3 mentions
#50
Introduction to Artificial Intelligence (AI)
In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks.
IBM
Rav Ahuja
0 reddit posts
1 mentions
#51
Data Engineering with Google Cloud Specialization
This program provides the skills you need to advance your career in data engineering and recommends training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.
Google Cloud
Google Cloud Training
0 reddit posts
5 mentions
#52
Machine Learning for Trading Specialization
This Specialization is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine...
Google Cloud
Jack Farmer
1 reddit posts
2 mentions
#53
Data Engineering with Google Cloud Professional Certificate
This program provides the skills you need to advance your career in data engineering and recommends training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.
Google Cloud
Google Cloud Training
0 reddit posts
8 mentions
#54
Introduction to Trading, Machine Learning & GCP
At the end of the course, you will be able to do the following: - Understand the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility - Identify the profit source and structure of basic quantitative trading strategies - Gauge how well the model generalizes its...
Google Cloud
Jack Farmer
1 reddit posts
0 mentions
#55
Computer Simulations
Big data and artificial intelligence get most of the press about computational social science, but maybe the most complex aspect of it refers to using computational tools to explore and develop social science theory.
University of California, Davis
Martin Hilbert
0 reddit posts
22 mentions
#56
Production Machine Learning Systems
In the second course of this specialization, we will dive into the components and best practices of a high-performing ML system in production environments.
Google Cloud
Google Cloud Training
0 reddit posts
2 mentions
#57
TensorFlow Specialization
Data and Deployment
Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.
deeplearning.ai
Laurence Moroney
0 reddit posts
2 mentions
#58
Image Understanding with TensorFlow on GCP
This is the third course of the Advanced Machine Learning on GCP specialization.
Google Cloud
Google Cloud Training
0 reddit posts
1 mentions
#59
Using Machine Learning in Trading and Finance
This course is for finance professionals, investment management professionals, and traders.
New York Institute of Finance
Jack Farmer
0 reddit posts
1 mentions
#60
AI for Medicine Specialization
AI is transforming the practice of medicine.
deeplearning.ai
Pranav Rajpurkar
0 reddit posts
4 mentions
#61
Intro to TensorFlow
We introduce low-level TensorFlow and work our way through the necessary concepts and APIs so as to be able to write distributed machine learning models.
Google Cloud
Google Cloud Training
0 reddit posts
1 mentions
#62
Advanced Machine Learning and Signal Processing
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ.
IBM
Romeo Kienzler
0 reddit posts
1 mentions
#63
Natural Language Processing in TensorFlow
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them.
deeplearning.ai
Laurence Moroney
0 reddit posts
2 mentions
#64
AI for Medical Diagnosis
AI is transforming the practice of medicine.
deeplearning.ai
Pranav Rajpurkar
0 reddit posts
1 mentions
#65
Machine Learning for Business Professionals
This course is intended to be an introduction to machine learning for non-technical business professionals.
Google Cloud
Google Cloud Training
0 reddit posts
1 mentions
#66
Getting Started with AWS Machine Learning
Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market.
Amazon Web Services
Blaine Sundrud
0 reddit posts
1 mentions
#67
Mathematics for Machine Learning
PCA
This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique.
Imperial College London
Marc Peter Deisenroth
0 reddit posts
2 mentions