Best of Coursera
Top Data Science Courses
These are the top 100 Data Science 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.
Machine learning is the science of getting computers to act without being explicitly programmed.
Stanford University
Andrew Ng
Andrew Ng
13 reddit posts
1193 mentions
1193 mentions
#2
Data Science
Specialization
Foundations using R
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
Foundations using R
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
2 reddit posts
137 mentions
137 mentions
#3
Data Science
Specialization
Statistics and Machine Learning
Build models, make inferences, and deliver interactive data products.
Statistics and Machine Learning
Build models, make inferences, and deliver interactive data products.
Johns Hopkins University
Brian Caffo, PhD
Brian Caffo, PhD
0 reddit posts
53 mentions
53 mentions
#4
Deep Learning
Specialization
If you want to break into AI, this Specialization will help you do so.
If you want to break into AI, this Specialization will help you do so.
deeplearning.ai
Andrew Ng
Andrew Ng
15 reddit posts
248 mentions
248 mentions
#5
Data Science
Specialization
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
Ask the right questions, manipulate data sets, and create visualizations to communicate results.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
3 reddit posts
389 mentions
389 mentions
#6
IBM Data Science
Professional Certificate
Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming.
Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming.
IBM
Alex Aklson
Alex Aklson
52 reddit posts
58 mentions
58 mentions
#7
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...
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
David Dye
2 reddit posts
97 mentions
97 mentions
#8
Applied Data Science with Python
Specialization
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.
University of Michigan
Christopher Brooks
Christopher Brooks
2 reddit posts
134 mentions
134 mentions
#9
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.
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
Laurence Moroney
4 reddit posts
38 mentions
38 mentions
#10
Advanced Machine Learning
Specialization
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods.
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
Evgeny Sokolov
4 reddit posts
61 mentions
61 mentions
#11
Machine Learning
Specialization
This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning.
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
Emily Fox
5 reddit posts
135 mentions
135 mentions
#12
Statistics with R
Specialization
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural ph...
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural ph...
Duke University
Mine Çetinkaya-Rundel
Mine Çetinkaya-Rundel
4 reddit posts
107 mentions
107 mentions
#13
R Programming
In this course you will learn how to program in R and how to use R for effective data analysis.
In this course you will learn how to program in R and how to use R for effective data analysis.
Johns Hopkins University
Roger D. Peng, PhD
Roger D. Peng, PhD
1 reddit posts
74 mentions
74 mentions
#14
Geographic Information Systems (GIS)
Specialization
Knowledge of Geographic Information Systems (GIS) is an increasingly sought after skill in industries from agriculture to public health.
Knowledge of Geographic Information Systems (GIS) is an increasingly sought after skill in industries from agriculture to public health.
University of California, Davis
Nick Santos
Nick Santos
3 reddit posts
57 mentions
57 mentions
#15
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.
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
Daphne Koller
3 reddit posts
40 mentions
40 mentions
#16
Genomic Data Science
Specialization
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets.
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets.
Johns Hopkins University
Steven Salzberg, PhD
Steven Salzberg, PhD
2 reddit posts
78 mentions
78 mentions
#17
Neural Networks and Deep Learning
If you want to break into cutting-edge AI, this course will help you do so.
If you want to break into cutting-edge AI, this course will help you do so.
deeplearning.ai
Andrew Ng
Andrew Ng
2 reddit posts
31 mentions
31 mentions
#18
Improving your statistical inferences
This course aims to help you to draw better statistical inferences from empirical research.
This course aims to help you to draw better statistical inferences from empirical research.
Eindhoven University of Technology
Daniel Lakens
Daniel Lakens
2 reddit posts
34 mentions
34 mentions
#19
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.
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
John C. Hart
0 reddit posts
45 mentions
45 mentions
#20
Big Data
Specialization
Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted.
Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted.
University of California San Diego
Ilkay Altintas
Ilkay Altintas
3 reddit posts
46 mentions
46 mentions
#21
Computational Neuroscience
This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function.
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
Rajesh P. N. Rao
0 reddit posts
29 mentions
29 mentions
#22
Introduction to Data Science in Python
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library.
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library.
University of Michigan
Christopher Brooks
Christopher Brooks
1 reddit posts
30 mentions
30 mentions
#23
Reinforcement Learning
Specialization
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI).
University of Alberta
Martha White
Martha White
2 reddit posts
13 mentions
13 mentions
#24
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.
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
Daphne Koller
2 reddit posts
22 mentions
22 mentions
#25
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.
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
David Dye
0 reddit posts
19 mentions
19 mentions
#26
Convolutional Neural Networks
This course will teach you how to build convolutional neural networks and apply it to image data.
This course will teach you how to build convolutional neural networks and apply it to image data.
deeplearning.ai
Andrew Ng
Andrew Ng
4 reddit posts
17 mentions
17 mentions
#27
Data Warehousing for Business Intelligence
Specialization
Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics.
Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics.
University of Colorado System
Michael Mannino
Michael Mannino
1 reddit posts
47 mentions
47 mentions
#28
Basic Statistics
Understanding statistics is essential to understand research in the social and behavioral sciences.
Understanding statistics is essential to understand research in the social and behavioral sciences.
University of Amsterdam
Matthijs Rooduijn
Matthijs Rooduijn
1 reddit posts
20 mentions
20 mentions
#29
How to Win a Data Science Competition
Learn from Top Kagglers
If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language process...
Learn from Top Kagglers
If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language process...
National Research University Higher School of Economics
Dmitry Ulyanov
Dmitry Ulyanov
1 reddit posts
12 mentions
12 mentions
#30
The Data Scientist’s Toolbox
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox.
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
1 reddit posts
22 mentions
22 mentions
#31
Business Analytics
Specialization
This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience.
This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience.
University of Pennsylvania
Eric Bradlow
Eric Bradlow
2 reddit posts
17 mentions
17 mentions
#32
Data Analysis and Interpretation
Specialization
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
Wesleyan University
Lisa Dierker
Lisa Dierker
0 reddit posts
57 mentions
57 mentions
#33
Sequence Models
This course will teach you how to build models for natural language, audio, and other sequence data.
This course will teach you how to build models for natural language, audio, and other sequence data.
deeplearning.ai
Andrew Ng
Andrew Ng
3 reddit posts
9 mentions
9 mentions
#34
Data Science at Scale
Specialization
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
Learn scalable data management, evaluate big data technologies, and design effective visualizations.
University of Washington
Bill Howe
Bill Howe
1 reddit posts
119 mentions
119 mentions
#35
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.
This online specialization provides participants a hands-on introduction to designing and building data pipelines on Google Cloud Platform.
Google Cloud
Google Cloud Training
Google Cloud Training
2 reddit posts
16 mentions
16 mentions
#36
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...
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
Google Cloud Training
1 reddit posts
11 mentions
11 mentions
#37
Statistical Inference
Statistical inference is the process of drawing conclusions about populations or scientific truths from data.
Statistical inference is the process of drawing conclusions about populations or scientific truths from data.
Johns Hopkins University
Brian Caffo, PhD
Brian Caffo, PhD
0 reddit posts
18 mentions
18 mentions
#38
Practical Machine Learning
One of the most common tasks performed by data scientists and data analysts are prediction and 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
Jeff Leek, PhD
0 reddit posts
16 mentions
16 mentions
#39
Learn SQL Basics for Data Science
Specialization
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency.
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency.
University of California, Davis
Sadie St. Lawrence
Sadie St. Lawrence
0 reddit posts
11 mentions
11 mentions
#40
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?...
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
Emily Fox
1 reddit posts
19 mentions
19 mentions
#41
Applied Machine Learning in Python
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods.
University of Michigan
Kevyn Collins-Thompson
Kevyn Collins-Thompson
0 reddit posts
13 mentions
13 mentions
#42
Data Visualization
Learn the general concepts of data mining along with basic methodologies and applications.
Learn the general concepts of data mining along with basic methodologies and applications.
University of Illinois at Urbana-Champaign
John C. Hart
John C. Hart
0 reddit posts
13 mentions
13 mentions
#43
Executive Data Science
Specialization
Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.
Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
2 reddit posts
16 mentions
16 mentions
#44
Recommender Systems
Specialization
A Recommender System is a process that seeks to predict user preferences.
A Recommender System is a process that seeks to predict user preferences.
University of Minnesota
Joseph A Konstan
Joseph A Konstan
0 reddit posts
14 mentions
14 mentions
#45
Managing Big Data with MySQL
This course is an introduction to how to use relational databases in business analysis.
This course is an introduction to how to use relational databases in business analysis.
Duke University
Daniel Egger
Daniel Egger
0 reddit posts
17 mentions
17 mentions
#46
Introduction to Probability and Data with R
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule.
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule.
Duke University
Mine Çetinkaya-Rundel
Mine Çetinkaya-Rundel
1 reddit posts
10 mentions
10 mentions
#47
Statistics with Python
Specialization
This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language.
This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language.
University of Michigan
Brenda Gunderson
Brenda Gunderson
2 reddit posts
10 mentions
10 mentions
#48
Data Visualization with Tableau
Specialization
In 2020 the world will generate 50 times the amount of data as in 2011.
In 2020 the world will generate 50 times the amount of data as in 2011.
University of California, Davis
Desiree' Abbott
Desiree' Abbott
0 reddit posts
11 mentions
11 mentions
#49
Introduction to Neurohacking In R
Neurohacking describes how to use the R programming language (https://cran.
Neurohacking describes how to use the R programming language (https://cran.
Johns Hopkins University
Dr. Elizabeth Sweeney
Dr. Elizabeth Sweeney
2 reddit posts
8 mentions
8 mentions
#50
Getting and Cleaning Data
Before you can work with data you have to get some.
Before you can work with data you have to get some.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
0 reddit posts
13 mentions
13 mentions
#51
Survey Data Collection and Analytics
Specialization
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains.
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains.
University of Maryland, College Park
Frauke Kreuter, Ph.D.
Frauke Kreuter, Ph.D.
0 reddit posts
15 mentions
15 mentions
#52
Data Visualization and Communication with Tableau
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member.
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member.
Duke University
Daniel Egger
Daniel Egger
0 reddit posts
17 mentions
17 mentions
#53
Mastering Software Development in R
Specialization
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians.
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians.
Johns Hopkins University
Roger D. Peng, PhD
Roger D. Peng, PhD
0 reddit posts
13 mentions
13 mentions
#54
Introduction to Big Data
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be.
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be.
University of California San Diego
Ilkay Altintas
Ilkay Altintas
0 reddit posts
10 mentions
10 mentions
#55
Julia Scientific Programming
This four-module course introduces users to Julia as a first language.
This four-module course introduces users to Julia as a first language.
University of Cape Town
Juan H Klopper
Juan H Klopper
2 reddit posts
5 mentions
5 mentions
#56
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,.
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
Emily Fox
0 reddit posts
14 mentions
14 mentions
#57
Reproducible Research
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner.
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner.
Johns Hopkins University
Roger D. Peng, PhD
Roger D. Peng, PhD
0 reddit posts
11 mentions
11 mentions
#58
Bayesian Statistics
From Concept to Data Analysis
This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data.
From Concept to Data Analysis
This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data.
University of California, Santa Cruz
Herbert Lee
Herbert Lee
0 reddit posts
9 mentions
9 mentions
#59
Bayesian Statistics
This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates.
This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates.
Duke University
Mine Çetinkaya-Rundel
Mine Çetinkaya-Rundel
1 reddit posts
21 mentions
21 mentions
#60
SQL for Data Science
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses.
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses.
University of California, Davis
Sadie St. Lawrence
Sadie St. Lawrence
0 reddit posts
9 mentions
9 mentions
#61
Data Manipulation at Scale
Systems and Algorithms
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it.
Systems and Algorithms
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it.
University of Washington
Bill Howe
Bill Howe
0 reddit posts
14 mentions
14 mentions
#62
Business Statistics and Analysis
Specialization
The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques.
The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques.
Rice University
Sharad Borle
Sharad Borle
1 reddit posts
7 mentions
7 mentions
#63
A Crash Course in Data Science
By now you have definitely heard about data science and big data.
By now you have definitely heard about data science and big data.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
1 reddit posts
6 mentions
6 mentions
#64
Exploratory Data Analysis
This course covers the essential exploratory techniques for summarizing data.
This course covers the essential exploratory techniques for summarizing data.
Johns Hopkins University
Roger D. Peng, PhD
Roger D. Peng, PhD
0 reddit posts
11 mentions
11 mentions
#65
Regression Models
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions.
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions.
Johns Hopkins University
Brian Caffo, PhD
Brian Caffo, PhD
0 reddit posts
10 mentions
10 mentions
#66
Algorithms for DNA Sequencing
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data.
We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data.
Johns Hopkins University
Ben Langmead, PhD
Ben Langmead, PhD
0 reddit posts
10 mentions
10 mentions
#67
Hadoop Platform and Application Framework
This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data.
This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data.
University of California San Diego
Natasha Balac, Ph.D.
Natasha Balac, Ph.D.
0 reddit posts
14 mentions
14 mentions
#68
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,.
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
Emily Fox
0 reddit posts
13 mentions
13 mentions
#69
Process Mining
Data science in Action
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques.
Data science in Action
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques.
Eindhoven University of Technology
Wil van der Aalst
Wil van der Aalst
1 reddit posts
12 mentions
12 mentions
#70
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.
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
Anna Potapenko
0 reddit posts
9 mentions
9 mentions
#71
Python for Genomic Data Science
This class provides an introduction to the Python programming language and the iPython notebook.
This class provides an introduction to the Python programming language and the iPython notebook.
Johns Hopkins University
Mihaela Pertea, PhD
Mihaela Pertea, PhD
0 reddit posts
11 mentions
11 mentions
#72
Practical Time Series Analysis
Welcome to Practical Time Series Analysis! Many of us are "accidental" data analysts.
Welcome to Practical Time Series Analysis! Many of us are "accidental" data analysts.
The State University of New York
Tural Sadigov
Tural Sadigov
0 reddit posts
8 mentions
8 mentions
#73
Applied Plotting, Charting & Data Representation in Python
This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library.
This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library.
University of Michigan
Christopher Brooks
Christopher Brooks
0 reddit posts
6 mentions
6 mentions
#74
Applied Social Network Analysis in Python
This course will introduce the learner to network analysis through tutorials using the NetworkX library.
This course will introduce the learner to network analysis through tutorials using the NetworkX library.
University of Michigan
Daniel Romero
Daniel Romero
0 reddit posts
7 mentions
7 mentions
#75
Econometrics
Methods and Applications
Welcome! Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making.
Methods and Applications
Welcome! Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making.
Erasmus University Rotterdam
Philip Hans Franses
Philip Hans Franses
0 reddit posts
5 mentions
5 mentions
#76
Text Retrieval and Search Engines
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets.
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets.
University of Illinois at Urbana-Champaign
ChengXiang Zhai
ChengXiang Zhai
0 reddit posts
8 mentions
8 mentions
#77
Text Mining and Analytics
This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or m...
This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or m...
University of Illinois at Urbana-Champaign
ChengXiang Zhai
ChengXiang Zhai
0 reddit posts
9 mentions
9 mentions
#78
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.
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
Igor Halperin
0 reddit posts
9 mentions
9 mentions
#79
Machine Learning
Clustering & Retrieval
Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend.
Clustering & Retrieval
Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend.
University of Washington
Emily Fox
Emily Fox
0 reddit posts
6 mentions
6 mentions
#80
Maps and the Geospatial Revolution
Learn how advances in geospatial technology and analytical methods have changed how we do everything, and discover how to make maps and analyze geographic patterns using the latest tools.
Learn how advances in geospatial technology and analytical methods have changed how we do everything, and discover how to make maps and analyze geographic patterns using the latest tools.
The Pennsylvania State University
Dr. Anthony C. Robinson
Dr. Anthony C. Robinson
0 reddit posts
8 mentions
8 mentions
#81
Data Management and Visualization
Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success.
Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success.
Wesleyan University
Lisa Dierker
Lisa Dierker
0 reddit posts
14 mentions
14 mentions
#82
IBM Applied AI
Professional Certificate
Artificial Intelligence (AI) is transforming our world.
Artificial Intelligence (AI) is transforming our world.
IBM
Rav Ahuja
Rav Ahuja
8 reddit posts
10 mentions
10 mentions
#83
Inferential Statistics
This course covers commonly used statistical inference methods for numerical and categorical data.
This course covers commonly used statistical inference methods for numerical and categorical data.
Duke University
Mine Çetinkaya-Rundel
Mine Çetinkaya-Rundel
0 reddit posts
5 mentions
5 mentions
#84
Bayesian Methods for Machine Learning
People apply Bayesian methods in many areas: from game development to drug discovery.
People apply Bayesian methods in many areas: from game development to drug discovery.
National Research University Higher School of Economics
Daniil Polykovskiy
Daniil Polykovskiy
0 reddit posts
8 mentions
8 mentions
#85
Regression Modeling in Practice
This course focuses on one of the most important tools in your data analysis arsenal: regression analysis.
This course focuses on one of the most important tools in your data analysis arsenal: regression analysis.
Wesleyan University
Jen Rose
Jen Rose
0 reddit posts
10 mentions
10 mentions
#86
Developing Data Products
A data product is the production output from a statistical analysis.
A data product is the production output from a statistical analysis.
Johns Hopkins University
Brian Caffo, PhD
Brian Caffo, PhD
0 reddit posts
6 mentions
6 mentions
#87
Data Analysis Tools
In this course, you will develop and test hypotheses about your data.
In this course, you will develop and test hypotheses about your data.
Wesleyan University
Jen Rose
Jen Rose
0 reddit posts
11 mentions
11 mentions
#88
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.
The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence.
IBM
SAEED AGHABOZORGI
SAEED AGHABOZORGI
0 reddit posts
11 mentions
11 mentions
#89
Introduction to Genomic Technologies
This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it.
This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it.
Johns Hopkins University
Steven Salzberg, PhD
Steven Salzberg, PhD
0 reddit posts
7 mentions
7 mentions
#90
Practical Reinforcement Learning
Welcome to the Reinforcement Learning course.
Welcome to the Reinforcement Learning course.
National Research University Higher School of Economics
Pavel Shvechikov
Pavel Shvechikov
1 reddit posts
6 mentions
6 mentions
#91
Genomic Data Science with Galaxy
Learn to use the tools that are available from the Galaxy Project.
Learn to use the tools that are available from the Galaxy Project.
Johns Hopkins University
James Taylor, PhD
James Taylor, PhD
0 reddit posts
6 mentions
6 mentions
#92
Bioconductor for Genomic Data Science
Learn to use tools from the Bioconductor project to perform analysis of genomic data.
Learn to use tools from the Bioconductor project to perform analysis of genomic data.
Johns Hopkins University
Kasper Daniel Hansen, PhD
Kasper Daniel Hansen, PhD
0 reddit posts
6 mentions
6 mentions
#93
Statistics for Genomic Data Science
An introduction to the statistics behind the most popular genomic data science projects.
An introduction to the statistics behind the most popular genomic data science projects.
Johns Hopkins University
Jeff Leek, PhD
Jeff Leek, PhD
0 reddit posts
6 mentions
6 mentions
#94
Interprofessional Healthcare Informatics
Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education.
Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education.
University of Minnesota
Karen Monsen, Ph.D., RN, FAAN
Karen Monsen, Ph.D., RN, FAAN
0 reddit posts
2 mentions
2 mentions
#95
Pattern Discovery in Data Mining
Learn the general concepts of data mining along with basic methodologies and applications.
Learn the general concepts of data mining along with basic methodologies and applications.
University of Illinois at Urbana-Champaign
Jiawei Han
Jiawei Han
0 reddit posts
4 mentions
4 mentions
#96
Practical Predictive Analytics
Models and Methods
Statistical experiment design and analytics are at the heart of data science.
Models and Methods
Statistical experiment design and analytics are at the heart of data science.
University of Washington
Bill Howe
Bill Howe
0 reddit posts
9 mentions
9 mentions
#97
Introduction to Data Analysis Using Excel
The use of Excel is widespread in the industry.
The use of Excel is widespread in the industry.
Rice University
Sharad Borle
Sharad Borle
1 reddit posts
5 mentions
5 mentions
#98
Linear Regression and Modeling
This course introduces simple and multiple linear regression models.
This course introduces simple and multiple linear regression models.
Duke University
Mine Çetinkaya-Rundel
Mine Çetinkaya-Rundel
0 reddit posts
4 mentions
4 mentions
#99
Relational Database Support for Data Warehouses
Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization.
Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization.
University of Colorado System
Michael Mannino
Michael Mannino
0 reddit posts
8 mentions
8 mentions
#100
Command Line Tools for Genomic Data Science
Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data.
Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data.
Johns Hopkins University
Liliana Florea, PhD
Liliana Florea, PhD
0 reddit posts
5 mentions
5 mentions