Top Data Science Courses Online

Data science is one of the hottest professions of the decade, and the demand for data analyst, data engineer and data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. On this page you will find various online courses offered by known universities and institutions that you can complete from comfort of your home. These courses will prepare you to take up Data Scientist, Data Engineer, Data Analyst, and Database Administrator roles on completion of these certifications. 

This page contains Affiliate Links for all courses displayed. 

This page contains affiliate links to online courses. Keep in mind that I may receive commissions when you click our links and make purchases. However, this does not impact my reviews and comparisons. I try our best to keep things fair and balanced, in order to help you make the best choice for you. The price of the product remains same for you whether I get a commission or not. 

1. Data Scientist Course Master Program

Offered by - Edureka

 Click Here to Access the Data Scientist Course Master Program
Professional Certificate : Beginner Level
Skills you will gain

Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib & 22 More Skills.

What you will learn
  1. 1
    You will learn the importance of Python in real time environment and will be able to develop applications based on Object Oriented Programming concept.
  2. 2
    You will learn conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning with R Programming Course and implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR
  3. 3
    Help you understand the different types of Machine Learning, Recommendation Systems, and many more Data Science concepts to help you get started with your Data Science career.
  4. 4
    Helps you master key Apache Spark concepts, with hands-on demonstrations. This Apache Spark course is fully immersive where you can learn and interact with the instructor and your peers. Enroll now in this Scala online training
  5. 5
    Help you master popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. In this Deep Learning training, you will be working on various real-time projects like Emotion and Gender Detection, Auto Image Captioning using CNN and LSTM, and many more.
  6. 6
    You will be working on real-life industry use cases in Retail, Entertainment, Transportation, and Life Sciences domains. Clear your Tableau Desktop, Analyst and Server certification exams with Tableau.
Time Required to Complete this Course

Approximately 6 to 8 months to complete. Suggested pace of 6 to 10 hours/week

2. Master of Science in Data Science

Offered by - UpGrad

 Click Here to Access the Master of Science in Data Science
Professional Certificate : Beginner Level
Skills you will gain

Statistics, Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data Analytics, 

What you will learn
  1. 1
    Complimentary Python Programming Bootcamp
  2. 2
    60+ Case Studies and Projects
  3. 3
    Personalised Industry Session &  Industry Readiness Assessments
  4. 4
    500+ Hours of Learning
Time Required to Complete this Course

Approximately 18 months to complete. Suggested pace of 15 hours/week

3. IBM Data Science Professional Certificate

Offered by - IBM

 Click Here to Access the IBM Data Science Professional Certificate
Professional Certificate : Beginner Level
Skills you will gain

Data Science, Deep Learning, Machine Learning, Big Data, Data Mining, Github, Python Programming, Jupyter notebooks, Rstudio, Methodology, Data Analysis, Pandas

What you will learn
  1. 1
    Learn what data science is, the various activities of a data scientist’s job, and methodology to think and work like a data scientist.
  2. 2
    Develop hands-on skills using the tools, languages, and libraries used by professional data scientists.
  3. 3
    Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python.
  4. 4
    Apply various data science skills, techniques, and tools to complete a project and publish a report.
Time Required to Complete this Course

Approximately 11 months to complete. Suggested pace of 3 hours/week

4. Introduction to Data Science Specialization

Offered by - IBM

 Click Here to Access the Introduction to Data Science Specialization
Specialization : Beginner Level
Skills you will gain

Data Science, Relational Database Management System (RDBMS), Cloud Databases, Python Programming, SQL, Deep Learning, Machine Learning, Big Data, Data Mining, Github, Jupyter notebooks, Rstudio

What you will learn
  1. 1
    Describe what data science and machine learning are, their applications & use cases, and various types of tasks performed by data scientists.
  2. 2
    Gain hands-on familiarity with common data science tools including JupyterLab, R Studio, GitHub and Watson Studio.
  3. 3
    Develop the mindset to work like a data scientist, and follow a methodology to tackle different types of data science problems.
  4. 4
    Write SQL statements and query Cloud databases using Python from Jupyter notebooks
Time Required to Complete this Course

Approximately 4 months to complete. Suggested pace of 3 hours/week

5. Advanced Data Science with IBM Specialization 

Offered by - IBM

 Click Here to Access the Advanced Data Science with IBM Specialization
Specialization : Advanced Level
Skills you will gain

Data Mining, Data Science, Internet Of Things (IOT), Deep Learning, Apache Spark, Statistics, Machine Learning, Long Short-Term Memory (ISTM)

What you will learn
  1. 1
    This gives you enough knowledge to take over the role of a data engineer in any modern environment.
  2. 2
    This gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines.
  3. 3
    This gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines.
  4. 4
    Completing Capstone Project has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability.
Time Required to Complete this Course

Approximately 4 months to complete. Suggested pace of 5 hours/week

6. Data Science Specialization

Offered by - John Hopkins University

 Click Here to Access the Data Science Specialization
Specialization : Beginner Level
Skills you will gain

Github, Machine Learning, R Programming, Regression Analysis, Data Science, Rstudio, Data Analysis, Debugging, Data Manipulation, Regular Expression (REGEX), Data Cleansing, Cluster Analysis

What you will learn
  1. 1
    Use R to clean, analyze, and visualize data.
  2. 2
    Navigate the entire data science pipeline from data acquisition to publication.
  3. 3
    Use GitHub to manage data science projects.
  4. 4
    Perform regression analysis, least squares and inference using regression models.
Time Required to Complete this Course

Approximately 11 months to complete. Suggested pace of 7 hours/week

7. Data Science: Statistics and Machine Learning Specialization

Offered by - John Hopkins University

 Click Here to Access the Data Science: Statistics and Machine Learning Specialization
Specialization : Intermediate Level
Skills you will gain

Machine Learning, Github, R Programming, Regression Analysis, Data Visualization (DataViz), Statistics, Statistical Inference, Statistical Hypothesis Testing, Model Selection, Generalized Linear Model, Linear Regression, Random Forest

What you will learn
  1. 1
    Perform regression analysis, least squares and inference using regression models.
  2. 2
    Build and apply prediction functions.
  3. 3
    Develop public data products.
  4. 4
    Understand the process of drawing conclusions about populations or scientific truths from data
Time Required to Complete this Course

Approximately 6 months to complete. Suggested pace of 6 hours/week

8. Data Science Fundamentals Specialization

Offered by - University of California, Irvine

 Click Here to Access the Data Science Fundamentals Specialization Course
Specialization : Beginner Level
Skills you will gain

Environmental Data Analysis, Data Documentation, Geophysical Data, Data Mining

What you will learn
  1. 1
    The knowledge and skills needed to work in the data science profession
  2. 2
    How data science is used to solve business problems
  3. 3
    The benefits of using the cross-industry standard process for data mining (CRISP-DM)
  4. 4
    The application of predictive modeling to professional and academic work
Time Required to Complete this Course

Approximately 4 months to complete. Suggested pace of 1 hour/week

9. Statistical Modeling for Data Science Applications Specialization

Offered by - University of Colorado, Boulder

 Click Here to Access the Statistical Modeling for Data Science Applications Specialization
Specialization : Beginner Level
Skills you will gain

Linear Model, R Programming, Statistical Model, Regression, Calculus and probability theory, Linear Algebra

What you will learn
  1. 1
    Correctly analyze and apply tools of regression analysis to model relationship between variables and make predictions given a set of input variables.
  2. 2
    Successfully conduct experiments based on best practices in experimental design.
  3. 3
    Use advanced statistical modeling techniques, such as generalized linear and additive models, to model wide range of real-world relationships.
Time Required to Complete this Course

Approximately 4 months to complete. Suggested pace of 9 hours/week

10. Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs Specialization

Offered by - Google Cloud

 Click Here to Access the Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs Specialization
Specialization : Beginner Level
Skills you will gain

Bigquery, Data Analysis, Data SQL, Data Management, Data Pipelines, Cloud Data, Fusion, Data ingestion, Data Processing, Data Visualization (DataViz), Tensorflow, Machine Learning

What you will learn
  1. 1
    Creating dataset partitions that will reduce cost and improve query performance.
  2. 2
    Using macros in Data Fusion that introduce dynamic variables to plugin configurations so that you can specify the variable substitutions at runtime.
  3. 3
    Building a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage.
  4. 4
    Using Google Cloud Machine Learning and TensorFlow to develop and evaluate prediction models using machine learning.
  5. 5
    Implementing logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset.
Time Required to Complete this Course

Approximately 1 month to complete. Suggested pace of 5 hours/week

11. Applied Data Science with Python Specialization

Offered by - University of Michigan

 Click Here to Access the Applied Data Science with Python Specialization
Specialization : Intermediate Level
Skills you will gain

Text Mining, Python Programming, Pandas, Matplotlib, Numpy, Data Cleansing, Data Virtualization, Data Visualization (DataViz), Machine Learning (ML) Algorithms, Machine Learning, Scikit-Learn, Natural Language Toolkit (NLTK)

What you will learn
  1. 1
    Conduct an inferential statistical analysis.
  2. 2
    Discern whether a data visualization is good or bad.
  3. 3
    Enhance a data analysis with applied machine learning.
  4. 4
    Analyze the connectivity of a social network
Time Required to Complete this Course

Approximately 5 months to complete. Suggested pace of 7 hours/week

12. Data Science Fundamentals with Python and SQL Specialization

Offered by - IBM

 Click Here to Access the Data Science Fundamentals with Python and SQL Specialization
Specialization : Beginner Level
Skills you will gain

Data Science, Github, Python Programming, Jupyter notebooks, Rstudio, Data Analysis, Pandas, Numpy, Ipython, Probability And Statistics, Regression Analysis, Data Visualization (DataViz)

What you will learn
  1. 1
    Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio.
  2. 2
    Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy.
  3. 3
    Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression.
  4. 4
    Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables
Time Required to Complete this Course

Approximately 6 months to complete. Suggested pace of 4 hours/week

13. Professional Certificate in Data Science

Offered by - Harvard University

 Click Here to Access the Professional Certificate in Data Science
Specialization : Beginner Level
Skills you will gain

R Programming, Statistical Concepts, Data Visualisation, Data Wrangling, Github, R Studio, Machine Learning

What you will learn
  1. 1
    Fundamental R programming skills
  2. 2
    Statistical concepts such as probability, inference, and modeling and how to apply them in practice.
  3. 3
    Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr
  4. 4
    Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio
  5. 5
    Implement machine learning algorithms
  6. 6
    In-depth knowledge of fundamental data science concepts through motivating real-world case studies
Time Required to Complete this Course

Approximately 1 year 5 months. Suggested Pace of 2 - 3 hours per week

14. Microsoft Azure Data Fundamentals Specialization

Offered by - Microsoft

 Click Here to Access the Microsoft Azure Data Fundamentals Specialization
Specialization : Beginner Level
Skills you will gain

Relational Data Azure, Core Data Concepts, Non-Relational Data Azure, Analytics Workload, Data Definition, Data Storage, Batching, Streaming, MS SQL, NoSQL, Power BI. 

What you will learn
  1. 1
    This Specialization is intended for IT professionals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.
  2. 2
    You will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores, and the processing options available for building data analytics solutions in Microsoft Azure. You will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight and learn what Power BI is, including its building blocks and how they work together.
  3. 3
    This Specialization is intended for IT professionals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure.
  4. 4
    You will explore relational data offerings, provisioning and deploying relational databases, and querying relational data through cloud data solutions with Microsoft Azure.
  5. 5
    In-depth knowledge of fundamental data science concepts through motivating real-world case studies
Time Required to Complete this Course

Approximately 4 months to complete. Suggested pace of 3 hours/week

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