Home » Certification » 10 Data Science Certification for Online Learning

10 Data Science Certification for Online Learning

Data Science Certification Courses

Top 10 Data Science Certification Programs

Data scientists are in high demand and for good reason. Organizations face a growing demand for data-driven professionals. As such, there is data science certification available for professionals who have a keen interest in working with data and creating value through its analysis.

Our Top 10 Picks

Udacity Logo
Data Scientist Nanodegree
Best project-based data science courses
Harvard University
Professional Certificate in Data Science
Best R data science certification
Udacity Logo
Programming for Data Science with Python Nanodegree
Best Python data science certificate
DataCamp
Data Scientist with Python
Best DIY type of data science courses
MicroMasters® Program in Statistics and Data Science
Best data science program for statistics
Dataquest
Data Scientist in Python
Best mid-range data science courses
IBM
Professional Certificate in IBM Data Science
Best IBM data science certificate
DataCamp
Data Scientist with R
Best data science courses for beginners
UC San Diego Logo
MicroMasters® Program in Data Science
Best data science certificate for advanced users
Udacity Logo
Data Science for Business Leaders Executive Program
Best courses for business executives

1. Data Scientist Nanodegree (Udacity)

Udacity Logo

Gain the skills you need to become a data scientist. With the help of the online Udacity Data Scientist Nanodegree program, you will advance your career in data science. From data analysis to machine learning, you’ll get challenged with real-world projects from industry experts like IBM and Kaggle.

In this 4-month program, you will learn how to design and build and deploy data pipelines. Next, you’ll get the skills you need to make informed decisions with data including design experiments and A/B testing. Finally, you’ll wrap up the program with an open-ended Data Science project reviewed by industry experts.

Courses

  1. Solving Data Science Problems – Take the plunge and learn the basics of data science so you can build effective data visualizations. This course is designed for data scientists who want to learn powerful data visualization and data analysis techniques.
  2. Software Engineering for Data Scientists – Get the skills you can understand software engineering and key concepts like Object-Oriented Programming (OOP). This course will teach you how to create unit tests, build classes, and more, so you can take the first step toward becoming a successful data scientist.
  3. Data Engineering for Data Scientists – Get started in data engineering today with this hands-on course. You’ll learn how to work with data in an interactive and efficient way, so you can build powerful solutions that have a positive impact on your business. Learn how to run pipelines, data transformation, and deployment in the cloud.
  4. Experiment Design and Recommendations – Get training on how to design and analyze A/B test results, explore approaches for building recommendation systems, and learn how to measure the effectiveness of your experiments.
  5. Capstone Project – Build your own open-ended data science project and get it reviewed with personalized feedback. This capstone project will give you a strong foundation for your future career in data science and that you can add to your portfolio.

Skills Acquired

  • Data Visualizations
  • Machine Learning
  • Software Engineering
  • Unit Tests
  • Building Classes
  • Data Engineering
  • Pipelines
  • Cloud Solutions Deployment
  • Experiment Design
  • A/B Testing
  • Recommendation Systems
  • IBM Watson Studio
  • Data Exploration

For more information, read our review of the Udacity Data Scientist Nanodegree.

PREREQUISITES: This program requires experience in Python, SQL, and statistics.

2. Professional Certificate in Data Science (Harvard University)

Harvard University

Get the skills you need to be a data scientist in R. Obtain a Professional Certificate in Data Science from one of the best schools in the world, Harvard University.

Gain the most relevant skills you need to analyze data and make informed decisions with data. This online program provides you with the fundamental skills you need to analyze and make decisions with data. You will learn how to use statistics, probability, inference, and modeling to make informed decisions.

Courses

  1. Data Science: R Basics – Take the first step to becoming a data scientist with this beginner-friendly course. Get started with R and learn everything you need to know to start analyzing data and making decisions.
  2. Introduction to Python Programming – Get a crash course in data visualization so you can start making beautiful charts and graphs with confidence. In this course, you will learn how to use ggplot2 to better visualize and analyze data.
  3. Data Science: Probability – Get a deep understanding of probability theory so you can solve complex data problems. This course is designed for data scientists who want to learn about the basics of probability and statistics so they can make sound decisions about data. This course involves a case study from the financial crash of 2007-2008.
  4. Data Science: Inference and Modeling – Get the skills you need to work with data and make informed decisions. Learn how to use inference and modeling to make sense of complex data.
  5. Data Science: Productivity Tools – Get a better understanding of the data science process and use GitHub, Unix/Linux, and RStudio to power your data analysis.
  6. Data Science: Wrangling – Learn how to process data and turn it into insights that can be used to make business decisions. Get started with this data wrangling course to get a deep understanding of how data is used to make decisions.
  7. Data Science: Linear Regression – First, you will learn how to use R to model data, build models, and analyze results. Finally, you will learn how to solve problems with linear regression and other modeling approaches.
  8. Data Science: Machine Learning – Get a better understanding of how machine learning is able to make predictions. In this course, you will use this knowledge to build a movie recommendation system and find the perfect movies for your audience.
  9. Data Science: Capstone – Wrap up everything you learned in a final capstone project. You will learn how to collect, analyze, model, visualize, and interpret data, and use these skills to improve your business or professional outcomes.

Skills Acquired

  • Data Science
  • R Programming
  • Probability
  • Inference
  • tidyverse
  • ggplot2
  • Data Wrangling
  • dplyr
  • RStudio
  • GitHub
  • Unix/Linux
  • Machine Learning
  • Data Exploration

INFORMATION: This self-paced program contains 9 skill-building courses over a period of one year and 5 months.

3. Programming for Data Science with Python Nanodegree (Udacity)

Udacity Logo

Get started in data science with this professional-level Programming for Data Science with Python Nanodegree. Throughout this program, you will learn essential Python programming methods for data analysis, manipulation, and presentation.

Get ahead in your career and learn the basics of programming so you can start coding right away. After completing this program, you will be able to use Python, SQL, Command Line, and Git to solve complex data-driven solutions.

Courses

  1. Introduction to SQL – Get the skills you need to answer complex business questions with SQL. First, this course will teach you how to use SQL to join, aggregate, and subqueries. Secondly, you will learn how to use SQL to answer common business questions. During the project, you will work with PostgreSQL to investigate a database.
  2. Introduction to Python Programming – Enhance your Python programming skills with this introductory course that covers everything from data structures, loops, and functions. First, you will learn how to build powerful applications with Python and leverage libraries like Numpy and pandas for data wrangling. During the project, you will explore US Bikeshare data and use descriptive statistics.
  3. Introduction to Version Control – Get a handle on version control and share your work with other data scientists in a simple and efficient way.  During the project, you will post your Jupyter Notebook to Github to foster collaboration.

Skills Acquired

  • Data Science
  • Python
  • SQL
  • PostgreSQL
  • GitHub
  • Version Control
  • Numpy
  • pandas
  • Data Structures
  • Loops
  • Functions
  • Jupyter Notebook
  • Data Exploration

PREREQUISITES: This program requires experience in Python, SQL, and statistics.

4. Data Scientist with Python (DataCamp)

DataCamp

Open up your data science world with this comprehensive course and get ready to tackle the most challenging hands-on problems with the Data Scientist with Python Career Path. You’ll learn the basics of data analysis, machine learning, and predictive modeling with Python, making it easier than ever to get started in this exciting field.

DataCamp’s philosophy is “learn by doing”. In this program, you’ll learn how to use the most popular Python libraries to build predictive models and perform hypothesis testing. You’ll also learn how to clean, manipulate, and visualize data so you can better understand it. This program is absolutely loaded with 34 units, from data manipulation to visualization.

Simplified Courses

  1. Introduction and Intermediate Python – Get the skills you need to analyze data in Python. Overall, this course covers the basics of data analysis, including data structures, data manipulation, data cleaning, and visualization with libraries like NumPy, pandas, and Matplotlib. Plus, you’ll learn how to write functions in Python and work with a variety of topics like dates, times, and exploratory data analysis.
  2. Data Visualization – Get a handle on the basics of data visualization, so you can create stunning visualizations that communicate your ideas and insights effectively. With this course, you’ll learn how to create custom visualizations in Matplotlib and Seaborn, and share them for feedback and discussion.
  3. Introduction to Statistics in Python – Get your statistical skills up and running and learn how to collect, analyze, and draw accurate conclusions from data. First, this course will teach you how to use Python to perform sampling, hypothesis testing, and make sound decisions. Next, you will get a better understanding of how statistics can be used to predict housing prices by using regression analysis.
  4. Supervised and Unsupervised Learning – Upgrade your machine learning skills with this interactive course that covers supervised and unsupervised learning in Python. In this course, you will learn how to make powerful predictions and extract insights from unlabeled datasets using scikit-learn and SciPy.

Skills Acquired

  • Data Science
  • Intermediate Python
  • NumPy
  • Pandas
  • Matplotlib
  • Data Visualization
  • Seaborn
  • Data Cleaning
  • Dates and Times
  • Writing Functions
  • Exploratory Data Analysis
  • Statistics
  • Regression
  • Sampling
  • Hypothesis Testing
  • Supervised Learning
  • Unsupervised Learning
  • Machine Learning
  • Tree-Based Models
  • Cluster Analysis

INFORMATION: This program contains 25 courses and 6 projects in a duration of 97 hours.

5. MicroMasters® Program in Statistics and Data Science (MIT)

MIT

Take the guesswork out of data analysis and prediction with our Master’s in Statistics and Data Science from the Massachusetts Institute of Technology. This 5 graduate-level course program will teach you how to analyze and predict big data using modern statistical models, as well as how to make use of machine learning in order to make better decisions.

If you’re looking to be a data engineer, scientist, or analyst, you can learn from the best in the business and get certified in statistics and data science. Get started with the MicroMasters® Program in Statistics and Data Science at MIT, and see the difference a well-certified program makes in decision-making.

Courses

  1. Probability: The Science of Uncertainty and Data – Get a handle on the basics of probability and data analysis, so you can build models that are more likely to succeed. Build your understanding of these concepts with this introductory course on probabilistic models.
  2. Fundamentals of Statistics – This course will help you develop a better understanding of how statistical inference works, how to assess the quality of evidence and how to make sound statistical decisions.
  3. Machine Learning with Python: From Linear Models to Deep Learning – Learn the basics of machine learning and apply it to real-world problems. This course will teach you how to work with deep learning and reinforcement learning using Python.
  4. Capstone Exam in Statistics and Data Science – Take this assessment and determine your level of expertise in statistics and data science. This final assessment will solidify that you have the skills you need to take on a professional data analysis project.
  5. Data Analysis Assessment (Select One) – The final course involves challenging yourself with selecting between 2 projects. First, you can assess your knowledge with data analysis for social science. Secondly, you could take on a project that involves the interplay between statistics and computation.

Skills Acquired

  • Data Science
  • Python
  • Statistics
  • Big Data
  • Machine Learning
  • Probabilistic Modeling
  • Bayesian Inference
  • Principal Component Analysis (PCA)
  • Clustering
  • Predictive Modeling
  • Supervised Learning
  • Unsupervised Learning
  • Regression

INFORMATION: This self-paced program contains 5 graduate-level courses over a period of one year and two months.

6. Data Scientist in Python (Dataquest)

Dataquest

Get the skills you need to succeed as a data scientist in the Data Scientist Career Path from Dataquest. This program is loaded with projects and courses to grow your career as a data scientist.

Some of the topics this program covers are web-scraping, data visualization, and data cleaning. By the end, you’ll be able to analyze data, help make business decisions, and use machine learning to solve complex problems.

Courses

  1. Introduction to Python – Take a step towards becoming a data analyst or data scientist with this introductory Python course. This course will teach you the basics of Python, from data analysis to data science. You’ll understand how to work with functions, dictionaries, loops, conditionals, and Jupyter Notebooks.
  2. Data Analysis and Visualization – This course will teach you how to analyze and visualize data using pandas and NumPy. You will also learn how to make data understandable, interpret statistics, and create beautiful graphs with Matplotlib.
  3. Data Cleaning – You will learn how to clean and analyze your data in pandas. This course will help you improve your data analysis skills, and make your data analysis process more efficient.
  4. The Command Line – This command line course provides an in-depth understanding of the basics of the command line. You will be able to use the command line to solve data science problems and learn essential Bash skills.
  5. Working with Data Sources – Get started with working with SQL databases and multi-table databases. You will also learn how to acquire data from APIs and web scraping in Python.
  6. Probability and Statistics – Get a better understanding of probability, distribution and variables so you can make better predictions. You’ll also learn about z-scores, Bayes’ theorem, and hypothesis testing.
  7. Machine Learning – Learn how to use machine learning to make better decisions. Get started with this comprehensive course which includes everything from linear regression to decision trees. Finally, it also covers deep learning, image classification, and a machine learning project.
  8. Advanced Topics in Data Science – Get a deep understanding of the latest data-driven innovations with this advanced course. You’ll learn about everything from Apache Spark to MapReduce.

Skills Acquired

  • Data Science
  • Python
  • Scikit-learn
  • Matplotlib
  • NumPy
  • pandas
  • SQL
  • Deep Learning
  • GitHub
  • UNIX command line
  • Data Visualization
  • Machine Learning
  • Data Exploration
  • Web Scraping
  • Predictive Modeling
  • Jupyter Notebooks
  • Data Analysis
  • Data Cleaning
  • Calculus
  • Linear Regression
  • Deep Neural Networks
  • Kaggle
  • Spark
  • MapReduce

INFORMATION: This self-paced program contains 35 courses and 26 projects over a period of one year and 9 months.

7. Professional Certificate in IBM Data Science (IBM)

IBM

Get a certificate that will show that you have learned some of the most important skills required to work in data science. In the Professional Certificate in IBM Data Science, you will gain hands-on experience with some of the most popular data science tools like Jupyter notebooks, Python, and RStudio.

This online certificate will teach you essential skills in data science, from data analysis to data modeling. Start your journey to becoming a Data Scientist with the help of IBM experts and learn the skills and techniques needed to tackle complex data problems.

Courses

  1. Introduction to Data Science – Take the first step in learning about data science and explore the world of data analysis with a real-world scientist. This course will give you the foundation you need to understand complex data sets, make informed decisions, and create useful insights.
  2. Data Science Tools – Learn about the world of data science first-hand from experienced data scientists and learn the latest software tools to analyze and interpret data.
  3. The Data Science Method – Get to know the basics of data science and how to manipulate it to get the most out of your data. Learn about the pitfalls of data analysis, learn about building models and predictive analytics, and more.
  4. SQL for Data Science – Learn how to use SQL to extract data from databases, and then use that data to create powerful business insights. This course is the perfect way to get up to speed with an important language in data science and learn how to apply it to real-world scenarios.
  5. Python Basics for Data Science – Start learning Python today and gain the skills you need to become a data scientist. This beginner-friendly course provides an introduction to Python for Data Science, with hands-on practice through lab exercises.
  6. Python for Data Science Project – Learn how to use data science tools to analyze and make informed decisions. This mini-project provides the foundation you need to create a dashboard in Python.
  7. Analyzing Data with Python – Learn how to analyze data in Python in this course. You will learn how to use multi-dimensional arrays, DataFrames, pandas, and scikit-learn to analyze data.
  8. Visualizing Data with Python – Get a crash course in Python to help you visualize data and make insights easy to understand. This course will teach you how to use Python to create visualizations that convey information in a clear, concise, and meaningful way.
  9. Machine Learning with Python: A Practical Introduction – Get up to speed with machine learning with this practical course, which covers the basics of supervised and unsupervised learning. You will learn how to predict trends with real-life examples.
  10. Data Science and Machine Learning Capstone Project – Gain the skills and knowledge you need to stand out with a portfolio project. Use feature engineering and use Python to validate a machine learning model.

Skills Acquired

  • Data Science
  • Python
  • SQL
  • IBM Watson Studio
  • RStudio IDE
  • Jupyter Notebooks
  • Skills Network Labs
  • pandas
  • Data Visualization
  • Matplotlib
  • Predictive Modeling
  • Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Regression

INFORMATION: This self-paced program contains 10 skill-building courses over a period of one year.

8. Data Scientist with R (DataCamp)

DataCamp

Get ahead in the data science field with the Data Scientist with R Career Track. This certificate provides the skills and knowledge you need to be a successful data scientist. You’ll learn all about R and how to use it to analyze, clean, manipulate, and visualize data.

You’ll get hands-on with popular R packages, including ggplot2 and tidyverse, and use real-world datasets to learn statistical and machine learning techniques. Learn by doing with DataCamp’s Data Science certification.

Simplified Courses

  1. Introduction and Intermediate Python – Get a taste of the world of R, the language of data analysis. Learn how to manipulate data structures and analyze complex data sets. Next, learn about conditional statements, loops, and vector functions. These tools will help you solve more complex R problems and improve your efficiency.
  2. Data Visualization – This course will introduce you to tidyverse, a powerful data science tool within R. You will learn how to visualize, analyze, and explore your data using the tidyverse in combination with tools like dplyr and ggplot2.
  3. Importing and Reporting – You’ll get started with R Markdown to easily create reports with dynamic data. This will make your reports more organized, easier to read, and more visually appealing. You will also learn how to read and import data from CSV, XLS, and text files in R.
  4. R Programming – This course covers the basics of writing functions in R, and leads you through examples and exercises to show you how to write reusable functions.
  5. Statistics and Data Exploration – This course will teach you how to use graphical and numerical techniques to explore the structure of your data in a systematic way. You’ll also learn how to make predictions and understand the results of regression analysis in order to make informed decisions.
  6. Machine Learning – Learn how to do unsupervised learning in R, a popular tool for data analysis. Plus, you will learn how to apply clustering and dimensionality reduction to data to improve accuracy.

Skills Acquired

  • Data Science
  • Intermediate R
  • Ggplot2
  • Tidyverse
  • Conditionals
  • Data Visualization
  • Loops
  • Data Manipulation
  • Dates and Times
  • Writing Functions
  • Exploratory Data Analysis
  • Statistics
  • Regression
  • Dpylr
  • R Markdown
  • Data Importing
  • Supervised Learning
  • Unsupervised Learning
  • Machine Learning
  • Random Forests
  • Cluster Analysis
  • Sgboost

INFORMATION: This program contains 22 courses with a duration of 88 hours.

9. MicroMasters® Program in Data Science (UC San Diego)

UC San Diego

Get hands-on experience in data science with the online MicroMasters® Program in Data Science. This program will guide you through the process of loading, cleaning, and analyzing data, so that you can make informed decisions about your business.

Throughout the 4 graduate-level courses from UC San Diego, you will be able to use Spark to analyze large-scale datasets. This program also covers machine learning, data visualization, and statistics.

Courses

  1. Python for Data Science – Learn how to manipulate, analyze, and visualize complex datasets with Python, pandas, and Matplotlib. This intensive course will teach you the basics of Python data science and how to use powerful open-source tools to achieve your goals.
  2. Probability and Statistics in Data Science using Python – Learn how to analyze, predict, and understand data using probabilistic and statistical methods. This course will teach you how to gain valuable insights from Python.
  3. Machine Learning Fundamentals – Learn how to use machine learning to make creative and accurate predictions, and make informed decisions based on data.
  4. Big Data Analytics Using Spark – Get a hands-on experience with big data analytics with Jupyter Notebooks. Finally, learn how to process large datasets using MapReduce, and use Spark to power your data analysis.

Skills Acquired

  • Data Science
  • Python
  • Statistics
  • Big Data
  • Machine Learning
  • Apache Spark
  • Jupyter Notebooks
  • MapReduce
  • Matplotlib
  • Pandas
  • Generative Models
  • Discriminative Models
  • Ensemble Methods
  • Deep Nets

INFORMATION: This self-paced program contains 4 graduate-level courses over a period of 10 months.

10. Data Science for Business Leaders Executive Program (Udacity)

Udacity Logo

Get off the beaten path a bit to advance your business with the Executive Program in Data Science for Business Leaders. This program will teach you how to leverage data at an orgy level to make strategic decisions, analyze complex data sets, and build powerful models that can change your business.

Learn how to use data science to drive business decisions and make informed decisions about where to invest your time and money. This executive program gives you the knowledge necessary to lead data science initiatives in your organization. 

Courses

  1. Introduction to Data Science – Get a clear understanding of the basics of Data Science and the potential it has to make your business operation more efficient. Learn how to use data to make decisions, see trends, and find solutions. 
  2. Business Case for Data Science – Learn how to make data science-driven decisions that will impact your business. This course will provide you with the knowledge and skills you need to begin building a data strategy that is successful.
  3. Human Capital of Data Science – Learn how to build a data science team that delivers value to the business. Explore how to recruit the best talent for your data science organization, and how to structure that team in order to deliver value to the business.
  4. Data and Machine Learning Infrastructure Strategy – Learn how to build a data and machine learning infrastructure to support your data science initiatives.  This course will help you understand the important parameters to develop a data science plan that meets the specific needs of your business.
  5. Build a 100-Day Data Plan (Capstone Project) – Get a plan that will help you achieve your business goals in 100 days. With this capstone project, you will know the steps you need to take to transform your business into a well-established data science organization.

Skills Acquired

  • Data Science
  • Business Case
  • Strategic Objectives
  • Data Strategies
  • Digital Transformation
  • Machine Learning Architecture
  • Data Architecture Strategy

PREREQUISITES: This program requires experience in statistics, probability, and business experience.

Key Takeaways

Although becoming a data scientist is an incredibly rewarding career path, it can also be one of the most challenging ones as well.

These data scientist certification programs ensure you have the most relevant training so you understand how to use industry-standard tools and techniques in the field.

Have you ever tried any of these data science certification courses before? If you have, we’d love to hear from you in our comment section below.

Related Certification Programs

Leave a Reply

Your email address will not be published. Required fields are marked *