FTC disclaimer: This post contains affiliate links and I will be compensated if you make a purchase after clicking on my link.
With 30 million plus registered users, Coursera has already become an established MOOC platform to learn topics of various genres.
Coursera is known for its quality material at affordable prices to help you keep updated on latest trends and technologies.
Is Coursera Free?
No. You need to pay a fee in order to get course certification (ranging from $29 to $95) for the courses you wish to study.
Some Coursera courses facilitate onetime payment fee that lasts for 180 days.
If you enroll to courses that are part of a specialization, you have to opt for monthly subscriptions.
Currently, there are around 200 plus big data Coursera courses with specializations in data science, machine learning, data analysis, probability and statistics.
All these courses are curated and taught by professors from world’s best universities.
If you are on a search for big data courses on Coursera, these handpicked courses can give you a better option to start with.
Best Coursera Big Data Course Online – Our Picks
1. Introduction to Big Data – University of Califirnia SanDiego
The introduction to big data Coursera course is part of the popular Big Data Specialization course offered by UC SanDiego.
Apart from English, you can learn the course with subtitles in Arabic, Korean, Hindi and Persian.
Course Ratings: 4.5+ from 4,459+ students
Key Learning’s from the Course:
- Core concepts behind Big Data problems, applications and systems.
- Get introduced to Hadoop framework
- Understand the big data problems with real world examples
- What are the V’s of Big Data and how to get value from these data using a 5 step process
- Architectural components and programming models necessary for data analysis
- Learn the features of core Hadoop stack components namely YARN, HDFS and MapReduce
- How to install and run a program using Hadoop framework.
Who is this course best suited?
For all those who are beginning their career in big data analytics and Hadoop should take this course. No programming experience is required though.
Skills Gained from the Course: Big Data, Apache Hadoop, Mapreduce and Cloudera
Course Reviews
2. Introduction to Data Science in Python – University of Michigan
This is a prerequisite course before studying advanced Coursera big data analysis courses.
Offered by University of Michigan, this is introductory course of the Applied Data Science with Python Specialization.
You can also learn this course in Chinese, Portuguese, Vietnamese, Korean and Hebrew.
Course ratings: 4.5+ from 8561+ students
Key Learning’s from the Course:
- Common Python programming functionalities, intro to data science and Jupyter notebook
- Pandas fundamentals for data cleaning and processing
- Read, query and index DataFrame structure with programming assignment
- Introduction to Statistical techniques like distributions, sampling and t-tests
- Understand lambdas techniques and manipulate csv files
- Ability to tabulate, clean and manipulate data and run a basic inferential statistical analysis
Who is this Course Best Suited?
For all those looking to get started with data manipulations in Python.
Skills Gained from the Course: Python Programming, Numpy, Pandas and Data Cleansing
Course Reviews:
3. Machine Learning – Standford
This is the most popular machine learning with big data Coursera course currently.
A broad introduction to machine learning, data mining and statistical pattern.
Available in English, Chinese, Hebrew, Spanish, Hindi and Japanese.
Course ratings: 4.9 + from 89,049+ students
Key Learning’s from the Course:
- Teach a machine how to learn concepts using data
- Applications of Linear regression and basic understanding of linear algebra
- Best practices for implementing linear regression
- Practice learning algorithms using Octave /Matlab
- Applications of Logistic Regression
- Machine learning models to regularise data
- Neural networks for digit recognition
- Apply machine learning to practice
- How to deal with skewed data
- Use of Support vector machines
- K-Means Algorithm for Data Clustering
- Introduction to Principal Component Analysis
- Gaussian distribution for anomaly detection
- ML algorithm applications with large datasets
Who is this Course Best Suited?
One of the best Coursera course to get you introduced to Machine Learning.
Skills Gained from the Course: Logistic Regression, Artificial Neural Network and ML Algorithms
Course Reviews:
4. The Data Scientist’s Toolbox – John Hopkins University
This course is part of the popular data science specialization course offered by John Hopkins University.
Available with subtitles in English, Arabic, French, Chinese, Greek, Italian, Portuguese, Vietnamese, Russian, Turkish, Hebrew and Japanese.
Course ratings: 4.5+ from 17,333+ students
Key Learning’s from the Course:
- Components of Data Science
- Install and set up R, Rstudio and Github repository
- Concepts of study design and turning data into knowledge
- Understand the data and its associated problems with course project
Who is this Course Best Suited?
For all those who want to start their career as a data scientist.
Skills Gained from the Course: Data Science, GitHub, R Programming and RStudio
Course Reviews:
5. Introduction to Probability and Data – Duke University
An introductory course to data sampling and data exploration, this is part of the Statistics with R specialization from Duke University
Available in English and Korean Language to learn.
Course ratings: 4.7+ from 2,622+ students
Key Learning’s from the Course:
- Introduction to probability and commonly used probability distributions
- Explore data through numerical summaries and visualizations
- Numerical and categorical data analysis
- Conditional probability, Bayes’ theorem and Bayesian inference
- Normal and the binomial distributions
- Solve real world data sets with data analysis project
Who is this Course Best Suited?
For all those looking for a basic statistics course to study at Coursera.
Skills Gained from the Course: Statistics, R Programming, Rstudio and Exploratory Data Analysis
Course Reviews:
6. Graph Analytics for Big Data – UC SanDiego
The graph analytics for big data Coursera course is part of the big data specialization course offered by UC San Diego.
Available only in English.
Course ratings: 4.2+ from 677+ students
Key Learning’s from the Course:
- Core mathematical properties of graph
- Use Graphical representation to solve big data problems
- Analyse graph using Neo4J
- Use of Cypher on graph networks
- Programming models and software frameworks used for graph analytics
Who is this Course Best Suited?
Anybody interested to learn graph analytics using Neo4J.
Skills Gained from the Course: Graph Theory, Neo4j, Analytics and Graph Database
Course Reviews:
7. Getting and Cleaning Data – Johns Hopkins University
A basic big data Coursera course to understand how to collect, clean and store data effectively.
The course is part of the data science specialization course from John Hopkins University.
Available in English, French, Chinese, Vietnamese and Russian
Course ratings: 4.6+ from 5,485+ students
Key Learning’s from the Course:
- Data cleaning basics to make data tidy
- How to obtain usable data from the web, APIs and databases
- Understand common data storage systems
- How to use R for text and data manipulation
Who is this Course Best Suited?
Data Scientist aspirants interested in learning programmatic data analysis.
Skills Gained from the Course: Data manipulation, REGEX, R Programming and Data Cleansing
Course Reviews:
Note: All Coursera courses come with a self-paced learning option, shareable certificates, practice quizzes, graded assignments with peer feedback. There are no refund policies at Coursera but you have a 7 days free trial to begin with.
Do you recommend any other big data Coursera courses worth enrolling into?
Happy Learning!
