The Best Online Data Science Courses, Classes, and Training

Data-driven technologies like automation and artificial intelligence are highly sought after today. More enterprises see the value in maximizing productivity and reducing spending. This is why data scientists are in high demand. If you want to venture into this rewarding field, enrolling in one of the best online data science courses can come in handy. 

There is a wide range of options to consider when it comes to choosing the best free online courses for data science. Data scientists are quickly becoming sought after experts in the field of technology after completing one of many available top data science courses online. Not only is it a fantastic major to study at the college level, but it’s also an exceptionally rewarding job. 

The Bureau of Labor Statistics reports that data scientists often earn over $158,000 per year. So, how can you pursue this career? Sure, you could major in data science or learn a programming language. But what if you just want to explore what it means to be a data scientist? 

You’re in luck. There are some great online data science courses that can teach you everything from the fundamentals to the most challenging concepts. These are all taught without applying to a degree program.

Below is a rundown of the critical responsibilities of a data scientist, along with the best online courses for you to learn data science.

What Is Data Science?

Data science combines programming, statistics, and mathematics to extract useful insights from data. Data scientists use machine learning algorithms to create artificial intelligence and data science systems that perform tasks without human interference. The systems are used to generate insights that are translated into tangible business decisions.

What Do Data Scientists Do?

Data scientists extrapolate data from studies and models to paint pictures. Data science is a great course if you like computer science, business, communication, statistics, and programming. Data science mainly deals with a few key aspects: big data, machine learning, data analytics, and data analysis. 

Questions to Ask Yourself Before Attending an Online Data Science Course

Which Aspects of Data Science Would You Like to Learn?

It is essential to research all aspects of data science before diving into a new educational program. As a result, you’ll be able to pick a specialization and gain a comprehensive understanding of the topic.

Does the program cover key concepts such as project prioritization, how to mesh data without primary keys, how to simplify complex databases, and how to develop robust and optimal systems? If the answer is yes, you have likely found the best bootcamp or online data science course to enroll in.

Should You Attend a Coding Bootcamp to Learn Data Science?

A data science bootcamp is an excellent place to learn data science skills. You will gain an immersive and accelerated understanding of the field in these programs. Before moving on to more advanced topics, the programs cover the basics. You can also gain relevant experience before entering the workforce through online data science bootcamps.

The Best Online Data Science Courses: An Overview

Online data science courses, classes, and training cover the essentials. Students in these programs should also participate in projects to practice their learning. The table below includes online coding bootcamps, massive open online courses (MOOCs), and university courses, along with their duration, cost, and certificate award. 

The Best Paid Online Data Science Courses

If you want to further explore data science, you have a variety of learning choices. There are many fantastic data science courses online curated by universities and community colleges to earn a degree or to earn a certificate in data science. However, there are also some excellent beginner options available online. Here are some of the best online data science courses.

Certificate in Data Science | California State University, Fullerton 

• Learning Format: Graduate-level certificate offering hands-on training 
• Level: Beginner 
• Subjects Covered: Introduction to analyzing data, introduction to programming basics for data science, data science, and machine learning

This data science certificate from California State University is ideal for professionals who want to use data to make better decisions. The curriculum covers how to present data results, apply statistical analysis, use modeling tools, and master the data analytics lifecycle. Students also learn how to use data to make better organizational decisions.

They also learn to translate business issues into analytical frameworks. This program covers five courses: statistical inference, data science I and II, data mining, machine learning, and computational data science. Students must complete a capstone project to showcase what they have learned during the course.  

Key Takeaway: Successful students earn nine continuing education credits that can be applied towards an advanced degree.

Certification of Professional Achievement in Data Sciences | Columbia University  

• Learning Format: Graduate-level certificate offering hands-on training 
• Level: Beginner 
• Subjects Covered: Algorithms for data science, machine learning for data science, probability, and statistics for data science

Students in this program complete five online courses. Some of the courses cover probability, algorithms, machine learning, and exploratory data analysis, as well as data visualization. Three courses in this lineup can be applied to an advanced degree at Columbia University. 

The curriculum covers the methods of data organization, such as queues, hashing trees, priority queues, and lists. Students also learn basic statistical principles and common algorithmic paradigms. The training covers algorithms for searching, basic graph models, matching, and streaming algorithms for data computation.

Key Takeaway: Successful students may be able to apply for credits from the program towards an advanced degree, such as an online master’s degree at this Ivy League university. 

Data Science Bootcamp | Data Science Dojo

• Learning Format: Immersive bootcamp program offering hands-on training
• Level: Advanced
• Subjects Covered: Data science fundamentals, predictive analysis, model evaluation and selection, ensemble methods, boosting, ranking and recommender systems, data engineering

This bootcamp offers online training for data engineers and data scientists. The program gives students access to pre-training tutorials that help them to prepare for classes. Students also get support for job seeking, interview prep, resume guidance, and portfolio creation.

The curriculum covers working with datasets using visualization and exploration techniques to tell stories. Students also practice techniques for clustering, regression, and text analytics using Python and R. They also master mathematical skills and fundamental statistics that data scientists need to thrive today. 

Key Takeaway: This program has different payment plans, so you can choose the one that meets your preference. The program also awards certificates of completion to all successful graduates. 

Data Scientist in Python | Dataquest

• Learning Format: Hands-on training using career-based curriculum
• Level: Beginner 
• Subjects Covered: Python programming, data analysis and visualization, data mining, web scraping, and APIs, Jupyter notebooks, command-line/bash

This program is ideal for both beginner and intermediate students. You don’t need a background in statistics to apply. The curriculum covers Python fundamentals, query databases with SQL, machine learning model building, data visualization and analysis, and basic statistics. These crucial skills ensure that students are prepared for the workplace.

Students learn about functional programming and object-oriented languages. The program also covers important libraries like Matplotlib, pandas, and NumPy. Students also learn about SQL queries and web scraping. They master basic skills in programming.

Key Takeaway: Students can access practice problems, a course catalog, an interactive community, and over 30 guided academic projects.

Graduate Certificate in Data Science | Elmhurst College  

• Learning Format: Graduate-level program  
• Level: Beginner 
• Subjects Covered: Data warehousing, introduction to business intelligence, quantitative methods

This course focuses on project management and data science. It is ideal for professionals looking for management jobs or others with similar credentials. Students take five courses in this online program. The courses cover data mining fundamentals and data-oriented approaches for business settings. Students also take a capstone project course.

The program can be completed within a year if students take two courses every term. These courses cover quantitative methods, business intelligence, data mining, and one elective. The best part about this program is that the credits can be applied to a master’s degree program. 

Key Takeaway: Students can complete five extra courses in the data science department and earn a master’s degree.

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Data Science Immersive Remote Flex | General Assembly 

• Learning Format: Immersive bootcamp program with a flexible schedule 
• Level: Beginner
• Subjects Covered: Data science fundamentals, machine learning models, exploratory data analysis

This program focuses on the skills data scientists need to extract data from complex datasets. Students get hands-on training as they learn exploratory data analysis, Python programming, and statistical modeling. The curriculum covers natural language processing, artificial intelligence, data science, machine learning algorithms, neural networks, and decision trees. 

This bootcamp has five projects for students to complete before they finish the program. This helps them to build a professional portfolio that contains data visualization and stakeholder presentations. Before the program ends, students also complete a capstone project and use machine learning models to address real-world challenges in the data science field.

Key Takeaway: Successful completion leads to a certificate. 

Graduate Certificate in Data Science | George Washington University

• Learning Format: Graduate-level program offering hands-on training
• Level: Beginner 
• Subjects Covered: Introduction to data science, data warehousing, and data mining

This graduate certificate is for professionals with an undergraduate degree. It requires 12 credits to complete, and the focus of the program is on underlying data systems, basics of data science, and how to document knowledge bases for data-intensive jobs. Students also learn data mining, statistical analysis, statistical computing, and machine learning. 

The credit earned after completing this program can be applied to a master’s degree program in data science at the university. The training method involves real-world experience and rigorous classwork. Students work with real-world problems from international companies, startups, and agencies in the data science field.

Key Takeaway: Credits from this certificate can be applied towards an advanced degree in data science. 

Graduate Certificate in Data Science | Indiana University Bloomington 

• Learning Format: Graduate-level Program  
• Level: Intermediate 
• Subjects Covered: Applied algorithms, introduction to NLP for data science, machine learning for signal processing

This graduate certificate is ideal for people who have some experience in data science. The online program requires 12 credits to complete. Students take four courses in a flexible setting. Some courses cover data mining, health and medicine, high-performance computing, and cloud computing.

The program uses a hands-on learning approach as students learn different data science principles. The curriculum covers machine learning, data visualization, data analysis, and cloud computing. Students who complete the program can take certification exams and find a job in the field.

Key Takeaway: The credits from this program can be applied towards an advanced degree at Indiana University Bloomington.

Data Science Bootcamp | NYC Data Science Academy 

• Learning Format: Hands-on Training
• Level: Intermediate
• Subjects Covered: Data Analytics with Python, Data Analytics with R, Business Cases in Data Science, Machine Learning

NYC Data Science Academy offers an intermediate program where students learn Python, R, and other analysis methods and tools. The training starts with a foundation level and progresses to advanced topics. Students learn to present research results using data visualization. 

After learning the foundational topics, students cover machine learning with Python. They also participate in real-world projects and master data science strategies and analytical methods. Students learn about big data and deep learning as well.

Key Takeaway: Students can access the alumni network and enjoy lifelong access to networking events and hiring seminars. 

Data Science Bootcamp | Thinkful

• Learning Format: Students learn through hands-on, practice-based learning.
• Level: Beginner 
• Subjects Covered: Analytics and Experimentation, Machine Learning: Supervised Learning

This online bootcamp focuses on essential data science topics like machine learning, Python, and SQL. Students learn the basics of Python and how to use it to find insights from extracted data. They also learn to design experiments for gathering new data and cover SQL for querying. 

Under the machine learning subject, students learn types of unsupervised models as well as clustering and feature reduction. Students build their own models and solve problems using time series analysis. The curriculum also covers deep learning models and how to analyze big data. They also explore specialization topics in data science.

Key Takeaway: Students enjoy live, personal video consultations even though the program is remote. It offers a self-paced learning experience.

Data Science A-Z: Real Life Data Science Exercises Included | Udemy

• Learning Format: Standalone Course
• Level: Beginner 
• Subjects Covered: SQL, SSIS, Tableau, Gretl, Clean and prepare data, Basic visualization, Modeling, Forecasting

Through hands-on real-life examples, students will learn how data scientists deal with real-world scenarios on a daily basis. In this course, the student is challenged by offering out-of-the-box data, projects, and modeling for self-practice. The course will provide students with in-depth knowledge of data science fundamentals as well as practical experience in the field.

Key Takeaway: Students will enjoy over twenty-one hours of lectures and video lessons while learning core concepts of data science and visualization.

Machine Learning, Data Science and Deep Learning With Python | Udemy

• Learning Format: Standalone Course
• Level: Intermediate
• Subjects Covered: Machine learning, deep learning, sentiment analysis, multiple regression, K-means clustering, reinforcement learning

Throughout this online data science course, you will learn techniques used by real data scientists and machine learning practitioners. More than 100 lectures spanning 15 hours of video comprise the comprehensive machine learning tutorial. Each concept is explained in plain English, avoiding the use of confusing mathematical notation and jargon.

Key Takeaway: This online data science course teaches students with prior programming experience to utilize key data science frameworks to create clean and transparent data models.

Data Science: Deep Learning and Neural Networks in Python | Udemy

• Learning Format: Standalone Course
• Level: Beginner
• Subjects Covered: Neural networks, classification, machine learning, TensorFlow, facial expression recognition

This course guides students through the process of creating an artificial neural network through deep learning. Students will gain a deeper understanding of the softmax function and backpropagation. Students will also use the TensorFlow library to assist in creating their neural network.

Key Takeaway: This online data science course provides students with a step-by-step guide to creating a neural network that can be used in their portfolio or to upskill in their current position within the data science field.

Data Science and Machine Learning Bootcamp With R | Udemy

• Learning Format: Standalone Course
• Level: Beginner
• Subjects Covered: R Basics, Matrices, Data frames, machine learning with R, data visualization, decision trees, logistic regression, K-means clustering, neural nets

This comprehensive online data science course provides students with the foundational skills and techniques they need to be successful in the data science field. Students will learn how to use the R programming language, neural networks, and machine learning to create stunning visualizations and models with data.

Key Takeaway: This full stack data science course allows students to gain in-depth knowledge of core data science concepts through hands-on learning and video lectures.

R Programming A-Z: R For Data Science With Real Exercises! | Udemy

• Learning Format: Standalone Course
• Level: Beginner
• Subjects Covered: Core programming principles, matrices, data frames, fundamentals of R, advanced visualization, GGPlot2

This course provides step-by-step instructions. Each tutorial builds upon what has already been learned and goes a step further. As soon as you view the videos, you will be able to apply valuable concepts. During this training, you will learn how to solve real-life analytical challenges. Several of these will be solved together, and others will be assigned as homework. This course is suitable for people without programming or statistics backgrounds.

Key Takeaway: This comprehensive course provides students with the fundamental techniques needed to successfully use R programming within the data science field.

The Best Free Online Data Science Courses

Although there are hundreds of amazing paid data science courses online, there are also comprehensive free data science courses online. These courses provide students with the same curriculum as expensive bootcamps, but at no cost. These free online data science courses are a great way to determine if this field is a good fit.

Data Science Specialization | Coursera

• Learning Format: 10-course introduction to data science
• Level: Beginner 
• Subjects Covered: The data scientist’s toolbox, R programming, exploratory data analysis

This course from Johns Hopkins University prepares you for a career in data science. The curriculum covers how to use R for data analysis and the installation and configuration of software for statistical programming. Students learn popular programming language concepts used in high-level languages. This course focuses on the exploratory techniques used in summarizing data. 

Students get a deeper understanding of why exploratory techniques are crucial for sharpening or eliminating potential hypotheses. They also learn about R and its plotting systems and data graphics construction. Before the course ends, students will be able to master multivariate statistical techniques so they can visualize high-dimensional data.

Key Takeaway: The course offers a shareable certificate that you can add to LinkedIn and share with potential employers and others in your network. 

Data Analysis and Presentation Skills: the PwC Approach Specialization | Coursera 

• Learning Format: Flexible program with hands-on training 
• Level: Beginner 
• Subjects Covered: Data-driven decision making, problem-solving with Excel, data visualization with advanced Excel

This course is offered by PricewaterhouseCoopers (PwC). PwC is a large company offering audit, consulting, and other financial services. This course focuses on data analysis and how to turn business intelligence into useful outcomes. 

Students learn to use important data analysis tools like PowerPoint and Microsoft Excel. They also cover data filtering and applications to solve problems faster and make better decisions. Students also learn to present data to engage the viewers and motivate them to act.

Python Basics for Data Science | edX

• Learning Format: Self-paced course 
• Level: Beginner 
• Subjects Covered: Python Data Structures, Python Programming Fundamentals, Working with Data in Python

This is a beginner-friendly course that introduces learners to Python for data science. The course aims to help learners master the Python programming language and give them an idea of what it entails to work with data in Python. Students participate in lab exercises, and by the end of the program, they will be able to create their own Python scripts.

The curriculum covers functions in using Pandas, defining variables, conditional statements and sets, and functions in Python. Students also learn how to write and read data and operate files in Python.

Key Takeaway: The program is self-paced and offers a shareable certificate for LinkedIn.

Data Science Foundations | IBM 

• Learning Format: Standalone Course  
• Level: Beginner
• Subjects Covered: Introduction to Data Science, Data Science Methodology, Data Science Tools

This course is offered by IBM through its Cognitive Class platform, which was previously known as Big Data University. This program focuses on the basics of data science. Students learn to program in R and use open source tools. They also engage in hands-on application of the skills they are learning.

The course is self-paced, so you can complete it on time. People with more experience may progress faster than others. The curriculum covers the main steps involved in solving data science problems, how data scientists think, and the steps involved in working in data science. This could include how to build a model, collect and analyze data, and research a problem.

Key Takeaway: The course is self-paced, so you can complete it at your own convenience.

Introduction to Machine Learning Course | Udacity

• Learning Format: Standalone Course 
• Level: Intermediate 
• Subjects Covered: Welcome to machine learning, Naive Bayes, and support vector machines

This course is for individuals with some experience in data science. The focus is on machine learning and its application in data science. The course teaches students to find and extract features representing the data they are working on. They also learn to determine the performance of a machine learning algorithm and crucial machine learning algorithms.

The curriculum covers how to code decision trees in Python, use MX scaler, preprocess data to improve algorithms and formulas for information gain and calculate and implement mini-projects to identify authors in emails with a decision tree in Python.

Key Takeaway: The training breaks down complicated topics in machine learning. 

Data Science Course Certificates vs Certifications

The main difference between a data science certification and a certificate is where and how it was received. Certificates are often awarded as evidence of attending a course or program. Certifications in data science require passing exams set by national organizations to ensure that you meet industry standards. 

Importance of Data Science Certifications

Data science certifications are important because they help you to remain updated on recent practices in the field. They also give you an edge over others as you develop the practical skills that employers are looking for. These certifications validate your skills, so hiring managers and recruiters know you are qualified for the job.

Data Science Certifications

Data science certifications are a great way to go one step further in your data science education and qualifications. A certification is a tangible certificate from an accredited institution that serves as proof of your educational background and data science skills. These certifications are valuable for resumes and potential employment. Below are some of the best data science certifications available online.

IBM Data Science Certification

This online data science certification teaches students the fundamental concepts of data science. It provides students with a deep dive into modern data science tools and the responsibilities of a data scientist. At the end of the certification course, students will be prepared to take a certification exam and earn a data science certification upon passing.

DASCA Senior Data Scientist

This certification is provided by the Data Science Council of America. This prestigious certification is only awarded to expert data scientists with over five years of industry experience. It is one of the two top certifications for data scientists in the world.

SAS Advanced Analytics Professional Certification

This professional certification can take many years to complete as it requires five other certifications. This comprehensive certification ensures data scientists understand the fundamentals and more complex topics of data science. Data scientists must have industry experience to begin working on this certification.

Data Scientist Nanodegree By Udacity

Although this is considered a nanodegree, it is respected as if it was a certification by the tech world. Top companies like Amazon, Google, and Microsoft value these nanodegrees, as they have the same strict requirements as similar data science certifications. Students and data scientists can enroll in this course if they possess basic knowledge of the field.

Professional Certificate In Data Science By Harvard University

This master’s level certification is comprised of 9 challenging courses. These courses test data scientists’ abilities and techniques to ensure they are top-tier. After students complete this certification, they will be able to add it to their resumes and grow within the workplace.

Online Data Science Classes, Training, or Courses: Which Is the Right Option?

Courses and training programs are ideal because they provide a practical learning environment and break down the topics from the basics. Individual courses and online classes are quite different. A good example of courses and training programs are coding bootcamps. They have a structured curriculum to ensure you learn the technical skills you need to thrive in the field.

How to Choose the Right Online Data Science Course, Class, or Training Program

Flexible Learning Schedule

Utilizing a flexible learning schedule can be helpful, especially if you already have a job. It isn’t ideal to enroll in a program that does not give you time to focus on other things in your life like work and school. The ideal program should be flexible in its pace and location.

With online courses, students can learn remotely without missing anything from the in-person classes. Part-time or self-paced programs can come in handy for busy, working professionals.

Structured Curriculum 

Not all programs offer a structured curriculum. Some courses, such as those from a coding bootcamp, do so with the input of employers in the data science field. This helps students learn what they need to land jobs in the field. 

With a structured curriculum, students learn progressively to ensure they grasp the basics before moving on. You may want to opt for a program that offers a structured curriculum from the start to the end so you won’t miss some crucial aspects of the subject.

Interactive Learning 

Most students enjoy practicing their learning by engaging in projects. A good program should include interactive learning measures to prepare students for their careers. Most courses and training use a project-based learning system. In some cases, the capstone projects make up part of the credit needed to complete the program.

Cost

Creating a reasonable budget is very important when researching online data science courses. This is because there are hundreds of comprehensive courses anywhere between $0 to $20,000. Each course provides the same robust curriculum but at a different cost. It is important to pick a course that is affordable and comprehensive for the best results.

Hands-On Training

Data science requires a lot of knowledge of different tools and techniques. Without this knowledge, a data scientist will struggle and underperform in the field. Knowing this, it is important to select an online data science course that provides students with practical hands-on training. Without this key implementation, students will miss out on a large part of their education and skill set.

Why You Should Take Online Data Science Courses or Classes

Pursuing a career in data science can be lucrative. According to the Bureau of Labor Statistics, computer and information research scientists have a median annual salary of $126,830. Mathematicians and statisticians have a median annual salary of $93,290. These professions can be accessed with data science skills through online data science courses. 

This list of courses and classes could lead you to your dream data science career. You can learn the skills you need to find a job or upskill. Most of the best online data science courses are flexible, so you can enroll and keep working.

With the help of these classes and talented instructors, you’ll be prepared to join the workforce or pursue a higher degree. Find a course that fits your needs and become a data science master.

Online Data Science Courses FAQ