Best Data Science Certification Courses & Training Online

In today’s digital age, data generation has skyrocketed, with over 2.5 quintillion bytes of data created daily. This surge in data across industries—ranging from social media to finance and healthcare—has made data science one of the fastest-growing and most lucrative career paths. In fact, data scientists in the U.S. earn an average salary of $127,637 per year, with demand expected to grow by 36% by 2031. Whether you’re entering the field or advancing your career, selecting the right Data Science certification is key to acquiring the skills needed to succeed in this competitive landscape.

Data Science involves expertise in programming, data manipulation, statistical analysis, machine learning, and data visualization. With a certification, you’ll gain hands-on experience in these areas and develop the ability to work with large datasets, derive insights, and drive decisions in organizations. Certification programs offer structured learning, mentorship, and industry-recognized credentials—essential for career growth.

Key Takeaways

• Data Science certifications teach core skills like Python programming, machine learning, and data analysis.
• Certification can boost credibility and earning potential. The average salary for certified professionals in the U.S. is $127,637.
• Top courses offer flexibility, real-world projects, and industry-recognized certifications.
• Supplement your learning with books, tutorials, and networking to deepen your expertise.

In this guide, we’ll highlight some of the top Data Science certification courses, breaking down their content and platforms and explaining why they can enhance your career. We’ll also share tips on selecting the best course and additional resources to help you stay ahead.

What is Data Science?

Data Science is the practice of extracting valuable insights and knowledge from structured and unstructured data using a combination of techniques from fields such as statistics, computer science, machine learning, and domain-specific expertise. It is an interdisciplinary field that uses processes, algorithms, and systems to understand large amounts of data.

The scope of Data Science includes, but is not limited to:

• Data Collection: Gathering data from diverse sources like databases, APIs, and cloud storage.
• Data Cleaning: Pre-processing raw data to ensure quality, consistency, and completeness.
• Data Analysis: Using statistical tools to uncover patterns, trends, and correlations within the data.
• Data Modeling: Applying machine learning models and algorithms to make predictions or uncover insights from datasets.
• Data Visualization: Presenting findings through graphs, dashboards, and interactive visualizations to communicate the story behind the data effectively.

Data Science is a driving force behind major innovations such as personalized recommendations on Netflix, self-driving cars, and predictive healthcare analytics. It’s no surprise that industries are scrambling to hire data-savvy professionals to help them harness the power of their data for better decision-making.

Why Pursue Data Science Certification?

There are several compelling reasons to pursue a Data Science certification. A recognized certification not only provides formal proof of your skills but also equips you with the knowledge required to apply data science techniques to real-world problems. Below are some key benefits:

1. Structured Learning

While many free resources are available online, a certification course provides structured, comprehensive training in core areas like Python programming, statistics, data visualization, machine learning, and data manipulation. These programs are designed to build a strong foundation and guide learners through advanced topics step by step.

2. Credibility

Obtaining a certification from a reputable institution or online platform enhances your credibility in the eyes of employers. It acts as proof that you’ve mastered the concepts and can apply them in practical scenarios, which is particularly valuable if you’re making a career switch to Data Science.

3. Better Career Opportunities

With businesses increasingly relying on data for decision-making, certified data scientists are in high demand. Certification opens doors to job roles like Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst, among others. The certification serves as a differentiator in a competitive job market.

4. Higher Earning Potential

Data scientists command impressive salaries. According to Glassdoor, the average annual salary for data scientists in the US is around $127,637. With a recognized certification and hands-on project experience, you can potentially earn higher than the industry average.

5. Networking and Community

Many certification programs offer access to online communities where you can connect with other learners, mentors, and industry professionals. These networks can be invaluable for career growth, providing job referrals, mentorship opportunities, and industry insights.

Criteria for Selecting the Best Data Science Course

Choosing the right Data Science certification course can make or break your learning journey. Before enrolling in a course, take into account the following criteria to ensure you select the best one suited to your needs:

1. Course Content and Curriculum

Look for courses that cover essential topics in data science, including:

• Python Programming
• Data Manipulation and Cleaning
• Machine Learning and Artificial Intelligence
• Data Visualization (with tools like Tableau or Matplotlib)
• Big Data Technologies (such as Hadoop and Spark)

Some courses are designed for beginners, while others cater to more advanced learners. Check the syllabus to ensure the course matches your current skill level and learning goals.

2. Course Duration

Online courses vary significantly in length, from short bootcamps lasting a few weeks to more comprehensive programs spanning several months. Select a course that fits into your schedule, whether it’s a self-paced option that allows flexibility or an intensive, instructor-led program.

3. Instructor Expertise

The quality of instruction can make a significant difference in your learning experience. Courses taught by experienced industry professionals or university professors often provide deeper insights into practical applications and industry trends. Research the instructor’s background and read reviews from past students to gauge the quality of teaching.

4. Hands-on Projects and Capstone Assignments

One of the best ways to solidify your learning is through hands-on projects. Look for courses that offer capstone projects, which allow you to work on real-world datasets and apply the concepts you’ve learned. This practical experience will be invaluable when building your portfolio.

5. Accredited Certifications

Make sure that the certification you are earning is from a reputable institution or organization. Recognized certifications hold more weight in the industry and are likely to boost your resume. Look for programs affiliated with renowned universities or respected platforms such as Coursera, edX, or Udacity.

6. Support and Mentoring

Some platforms offer added benefits, such as mentoring, career coaching, and support forums. This additional guidance can help you stay motivated and overcome challenges during your learning journey. Look for courses that provide support, especially if you’re new to data science.

Top 6 Data Science Certification Courses

1. Dooey Data Science Certification Course With Python

Data science experts have recommended this course as one of the best because of what it delivers. Besides this, the course has so far enrolled 3475 learners, with 1079 of them giving it a rating of 4.2/5! So, what does this leading course cover? It trains you to master data science and analytics techniques while using Python. You’ll cover the essential concepts in Python programming. The course also delves into details of machine learning, data analytics, data visualization, NLP, and web scraping.

Dooey Data Science Training Course Highlights and Features

• The course instructor is Alvaro Fuentes, a data scientist and founder of Quant Company. He has many years of teaching in the field of data science
• Interactive and detailed learning lasting up to 68 hours
• Self-paced and instructor-led online flexi-pass learning available for individuals
• Corporate training packages are also available on demand
• Self-paced eLearning course content available
• Mentoring sessions by industry experts are available
• 4 real-world projects covering industry-based domains in telecom and the stock market, among others
• You’ll have the access of a lifetime to self-paced learning

Pros of the Dooey Data Science Certification Course

• Highly Rated Course: With a solid rating of 4.2/5 from 1,079 learners and an enrollment of 3,475 students, this course is well-regarded in the data science community. The positive feedback reflects the effectiveness of the curriculum and teaching methods, making it a trusted choice for aspiring data scientists.
• Comprehensive Curriculum: The course covers essential data science concepts, including Python programming, machine learning, data analytics, data visualization, natural language processing (NLP), and web scraping. This broad range provides learners with a robust foundation, ensuring they have the skills necessary to tackle various data science challenges in real-world scenarios.
• Flexible Learning Options: Students can choose between self-paced and instructor-led options, which accommodate different learning styles and schedules. This flexibility allows learners to balance their studies with other commitments, such as work or family responsibilities. Additionally, corporate training packages are available for organizations looking to enhance their teams’ data science capabilities.
• Lifetime Access: Enrolling in this course grants learners lifetime access to all course materials. This is beneficial for revisiting complex topics or staying updated on new developments in data science, which is crucial in a rapidly evolving field.

Cons of the Dooey Data Science Certification Course

• Lengthy Course Duration: At 68 hours, the course may be extensive for learners with limited time availability. Some may find it challenging to allocate sufficient time to complete all modules, especially if they are juggling multiple responsibilities.
• Prerequisite Knowledge Required: The course may require some familiarity with Python or basic data science concepts. Complete beginners could find it challenging to keep pace without a foundational understanding, potentially hindering their learning experience.
• Limited Networking Opportunities: While there are mentoring sessions, the course lacks a more extensive community or forum for peer interaction. This could limit opportunities for networking and collaboration, which are valuable in the data science field.
• Cost Considerations: The course’s pricing might be relatively high compared to other options, which could deter potential learners, especially those looking for affordable certification pathways.

2. Coursera Data Science Certification Course

The Introduction to Data Science in Python Course from Coursera is undoubtedly such a great course. With a rating of 4.5/5 by 9,871 learners and 2,336 reviews, this course comes highly recommended! But why is this the case? This is because the course takes you through Python programming from scratch. And that’s not all! Christopher Brooks, a leading data science specialist, delivers this course. Through his guidance, you’ll master techniques like lambdas, how to read and manipulate CSV files, and the details of the NumPy library. Some skills you’ll gain from this Data Science tutorial include Python Programming, Numpy, Pandas, and Data Cleansing.

Coursera Data Science Certification Course Highlights and Features

• It’s the 1^st of 5 courses in Applied Data Science with Python Specialization
• Intermediate level
• It’s 100% online
• Self-paced online course
• 4 course modules delivered through 29 video lectures taking up to 4 weeks
• Flexible and convenient learning, depending on your schedule
• You’ll take about 19 hours to complete the course
• Includes course videos, quizzes, graded assignments, and quizzes with feedback
• Access to graded programming-related assignments
• A real-world data science-based course project at the end of the course
• The course is delivered in English with subtitles, Traditional Chinese, Vietnamese, Portuguese (Brazilian), Korean and Hebrew
• A completion certificate is issued at the end of the course
• Financial aid is available for learners who can prove that they are truly deserving

Pros of the Coursera Data Science Certification Course

• High Ratings and Reviews: This course boasts an impressive rating of 4.5/5 from 9,871 learners, showcasing its popularity and effectiveness. The extensive number of reviews indicates a wealth of student experiences, helping potential learners gauge the course’s quality.
• Structured Learning Path: As the first of five courses in Applied Data Science with Python Specialization, learners can progress systematically through advanced topics. This structured approach enhances understanding as each course builds on the previous one, ensuring comprehensive coverage of data science concepts.
• Diverse Learning Materials: The course includes various educational formats, such as videos, quizzes, and programming assignments, catering to different learning styles. This diverse approach helps students grasp complex concepts effectively and ensures they can apply their knowledge practically.
• Accessibility and Flexibility: Because it is 100% online and self-paced, students can learn according to their schedules. This flexibility is particularly beneficial for those balancing other commitments, allowing for a more personalized learning experience.

Cons of the Coursera Data Science Certification Course

• Intermediate Level: The course is categorized as intermediate, which may not suit complete beginners without prior knowledge of Python or programming. This requirement could deter those who are just starting their data science journey.
• Time Commitment: With approximately 19 hours of content to complete, the course may require a significant time investment. For learners with busy schedules, this could be a barrier to completion.
• Limited Real-World Application: While the course covers theoretical aspects, some students may feel it lacks in-depth real-world project experience. Practical application is crucial in data science, and this perceived gap might hinder students’ preparedness for actual job scenarios.
• Financial Aid Availability: Although financial aid is an option, the application process can be cumbersome and may not suit everyone seeking immediate enrollment. This could lead to delays for those needing assistance.

3. Edureka Data Science Course with Python

This is among the leading Data Science Programs that can never be ignored! This is demonstrated by a whopping 37,000+ learners satisfied by this course. And we won’t forget the 4.57/5 rating by 5000 of these students! The course allows you to learn the basics of Python and master major concepts of Python programming, such as file operations, data operations, and object-oriented programming. You’ll also come across several Python libraries, including Numpy, Pandas, and Matplotlib, which are essential aspects of data science.

Edureka Data Science Certification Course Highlights and Features

• Live instructor-led training sessions lasting up to 42 hours. The instructors are experts in Data Science
• Real-life projects and case studies that involve how to implement Data Science using Python
• Every class session consists of practical assignments totaling up to 60 hours for the whole course
• Lifetime access to the LMS (Learning Management System). This includes class presentations, installation guides, quizzes, and class recordings
• 60-day access to cloud labs. The labs are designed to help you obtain hands-on skills in an environment that’s already pre-configured
• The highlight of this course is the hands-on project that you’ll work on
• 24/7 online expert support
• Access to an online community forum
• A certification will be awarded upon the successful completion of the course.

Pros of the Edureka Data Science Course with Python

• Outstanding Student Satisfaction: With over 37,000 learners and a rating of 4.57/5, this course demonstrates strong student satisfaction and positive learning outcomes. The high enrollment and ratings suggest a well-structured and effective curriculum.
• Live Instructor Interaction: The course offers live instructor-led sessions, providing learners with real-time feedback and interaction. This feature can enhance understanding and engagement, making complex topics more approachable and allowing for immediate clarification of doubts.
• Hands-On Experience: Students engage in real-life projects and case studies, allowing them to apply their knowledge practically. This hands-on experience is crucial for mastering data science skills, as it prepares students for the challenges they will face in the workforce.
• Comprehensive Learning Management System: With lifetime access to the Learning Management System (LMS), students benefit from resources such as class presentations, installation guides, quizzes, and recordings. This promotes continuous learning and allows students to revisit materials as needed.

Cons of the Edureka Data Science Course with Python

• Intensive Course Schedule: The 42-hour course duration may require a significant time commitment. Balancing work, family, and study might be challenging for learners, potentially leading to burnout.
• Focus on Python Only: While Python is essential for data science, the course primarily focuses on this language. This limited exposure may restrict learners from gaining familiarity with other critical tools and languages commonly used in the field.
• Limited Flexibility: The live sessions may not fit into everyone’s schedule, especially for those who prefer learning at their own pace. This could lead to missed content and hinder the overall learning experience.
• Support Quality Variation: While 24/7 expert support is available, the quality and speed of responses can vary based on the instructor’s or support staff’s availability. Inconsistent support may lead to frustration for learners needing immediate assistance.

4. Pluralsight Data Science Certification Course with Python

This Pluralsight course is among the best in data science, with Python courses that will equip you with advanced knowledge to help you become a data scientist. This leading course has been rated at 4.9/5 by over 138 learners. With the help of Abhishek Kumar, the expert course instructor, you’ll become experienced in working on data science projects that include processing data and how to build and evaluate machine learning models. Using Python libraries, you’ll understand how to expose the ML model as a general API.

PluralSight Data Science Course Highlights and Features

• The instructor is a consultant in Data Science
• Course duration: 6 hours, 25 minutes
• This online course is divided into 8 modules
• Includes interactive learning sessions, projects, and practice exams
• Beginner level
• Includes a case study to prepare you to develop and execute data science projects successfully
• Includes personal and premium plans
• The personal plan includes the course library, learning paths, course discussions, skill and IQ testing, exercise files, online and offline course viewing, and a course completion certificate.
• The premium plan includes all the features of the personal plan, interactive courses, practice exams, and projects.

Pros of the Pluralsight Data Science Certification Course

• Exceptional Rating: With a rating of 4.9/5 from over 138 learners, the course is highly regarded for its quality and effectiveness in teaching data science principles. Such a high rating indicates that students find the course beneficial and well-structured.
• Concise Course Duration: At 6 hours and 25 minutes, the course is relatively short, making it accessible for learners seeking a quick yet comprehensive introduction to data science. This brevity is ideal for professionals looking to enhance their skills without a long-term commitment.
• Expert Instructor: The course is led by Abhishek Kumar, a Data Science consultant with extensive industry experience. His expertise enriches the learning experience, as he provides real-world insights and practical applications of data science concepts.
• Flexible Learning Plans: Pluralsight offers both personal and premium plans, allowing learners to choose options that best suit their needs and budget. This flexibility in pricing and access is beneficial for individuals and teams alike.

Cons of the Pluralsight Data Science Certification Course

• Beginner-Level Focus: As a beginner-level course, it may not provide enough depth for learners who already have experience in data science or Python programming. More advanced students might find the content too simplistic and not challenging enough.
• Limited Interactivity: While it includes projects and practice exams, some learners may find the level of interactivity lacking compared to other courses that offer live sessions and collaborative learning opportunities. This could lead to a less engaging learning experience.
• Subscription Model: The course requires a subscription, which may become costly over time for learners looking to access multiple courses or extended materials. This recurring expense could deter some from enrolling.
• One-Project Limitation: Access to only one project file may restrict hands-on practice, which is essential for skill development in data science. Learners may desire more opportunities to work on diverse projects to strengthen their portfolios.

5. LinkedIn Data Science Certification Course with Python

This amazing Python for Data Science course qualifies as one of the best certification courses due to its unique features. It has been viewed by over 179,490 learners, with 8920 of them approving it as the best. The course starts with the basics of Jupyter notebooks and takes you through data visualization, analysis, and machine learning and its methods. Other topics include data clustering, classification methods, and how to create plot.ly charts.

LinkedIn Learning Data Science Course Highlights and Features

• A Big Data and Data Science Strategist, Lillian Pearson, will take you through the course. She’s also the Data Mania LLC founder and a publisher of leading Big Data educational materials
• 100% online course
• Offline viewing available
• The course is 6 hours, 32 minutes long
• You’ll obtain skills in Python Programming, Machine Learning, Data Visualization, and Data Modelling.
• You’ll learn how to simulate a social network using NetworkX
• Access to one project file
• 11 quizzes in all coming at the end of every chapter
• You can access the course through your phone or tablet
• A completion certificate is awarded once you complete the course successfully
• A free 1-month trial

Pros of the LinkedIn Data Science Certification Course

• Wide Reach and Recognition: Viewed by over 179,490 learners with 8,920 approvals, this course has a significant following and credibility within the data science community. Such widespread recognition reflects the course’s perceived value among professionals.
• Comprehensive Skill Development: The course covers a broad range of topics, including data visualization, analysis, and machine learning. This comprehensive approach equips learners with essential skills required in the job market, enhancing their employability.
• Flexible Learning Format: Because the course is 100% online, students can learn at their own pace, making it easier to fit the course into busy schedules. This flexibility is particularly appealing for professionals looking to upskill while maintaining their current roles.
• Mobile Accessibility: The course can be accessed through mobile devices, allowing for convenient learning on the go. This feature is particularly beneficial for individuals who travel frequently or prefer to study during their commutes.

Cons of the LinkedIn Data Science Certification Course

• Short Duration: At 3 hours and 45 minutes, the course might be perceived as too brief for some learners, particularly those seeking in-depth knowledge of data science. This condensed format may lead to gaps in understanding complex concepts.
• Limited Practical Application: While the course offers theoretical knowledge, some learners may feel that it lacks extensive hands-on projects, which are crucial for mastering data science skills. This could leave students unprepared for real-world applications.
• Basic Coverage: The course is primarily introductory and may not provide sufficient depth for learners who are already familiar with data science concepts or Python. More advanced learners might find the content repetitive or too elementary.
• Networking Limitations: Although there is potential for networking through LinkedIn, the course itself does not facilitate community interaction among students, which could limit collaborative learning opportunities.

6. Springboard Data Science Certification Course & Bootcamp

Topping our list is the Springboard’s Data Science course. The course that has enrolled about 800 students has one of the highest ratings at 4.88/5! The course instructor ensures you go beyond mastering skills such as statistics, visualization, and data wrangling. You’ll learn how to become a machine learning expert. The course covers advanced forms of data science concepts such as machine learning and inferential statistics. You’ll also acquire practical mastery in building data products that integrate with various product-grade-based software.

SpringBoard Data Science Bootcamp Training Course Highlights and Features

• The course is delivered by a leading data science expert with many years of experience in the field.
• It is highly recommended that you have knowledge of probability and statistics and experience in at least one programming language before beginning the course.
• The course is self-paced and is delivered online
• Course completion in about 6 months
• The extensive course takes up to 140 hours. This includes over 60 hours of industry-specific projects.
• You’ll learn about programming tools like Python, Pandas, Git, and Github. You’ll also cover data wrangling, data stories, inferential statistics, and machine learning.
• At the end of the course, you’ll have access to various career resources and learn the techniques to help you stand out and easily find data science-related jobs.
• Get a data science job within 6 months of graduating or your money back with one of the best job guarantees on the market.
• Gain hands-on experience by working through 14 real-world projects to develop your data science portfolio.
• Unlimited 1:1 mentor support. Meet weekly with your mentor to get important feedback.
• You’ll receive a certificate of completion once you finish the course successfully.

Pros of the Springboard Data Science Certification Course

• Strong Enrollment Numbers: With over 18,300 students enrolled, the course demonstrates its popularity and effectiveness among learners. The high enrollment indicates a strong reputation in the field of data science education.
• Comprehensive Learning Experience: The course provides in-depth coverage of various data science topics, including R, Python, and machine learning, ensuring that learners acquire a diverse skill set. This comprehensive approach prepares students for a wide range of challenges in data science.
• Live Instructor-Led Sessions: Featuring live virtual classrooms, students benefit from real-time interactions with instructors, enhancing understanding and providing immediate feedback on queries. This interactive element can significantly improve the learning experience.
• Capstone Projects: The inclusion of capstone projects allows learners to apply their knowledge in real-world scenarios, solidifying their skills and enhancing their portfolios. This practical experience is crucial for building confidence and competence in data science.

Cons of the Springboard Data Science Certification Course

• Lengthy Course Duration: The course spans approximately 40 hours, which may require a substantial time commitment. For some learners, especially those with demanding schedules, this could pose a challenge to completion.
• Prerequisite Knowledge Required: While the course covers a wide range of topics, it may assume some prior knowledge of programming or data science principles. Complete beginners might struggle to keep up with the pace and content complexity.
• Higher Cost: The course’s pricing might be higher than that of other certifications, potentially deterring learners with budget constraints. This higher cost may limit access for some individuals interested in pursuing data science.
• Varied Quality of Instructors: While many instructors are knowledgeable, the quality of teaching may vary. This inconsistency could impact the learning experience, as some students may not receive the same level of support or expertise.

Additional Resources to Boost Your Learning

In addition to enrolling in a certification course, there are several other ways to supplement your data science education and further deepen your understanding of the subject.

1. Books

• Python for Data Analysis by Wes McKinney: A practical guide on using Python for data manipulation and analysis, written by one of the most prominent figures in the Python community.
• Data Science from Scratch by Joel Grus: Provides a solid understanding of core data science principles, focusing on machine learning and statistical techniques from the ground up.

2. Online Tutorials

• Kaggle: A leading platform for data science competitions and learning. It offers tutorials and datasets for hands-on learning, providing an opportunity to work on real-world challenges.
• GitHub: Explore open-source data science projects, collaborate with others, and contribute to existing projects to improve your practical knowledge.

3. YouTube Channels

• Sentdex: A popular YouTube channel that covers Python programming, data science tutorials, and machine learning.
• StatQuest with Josh Starmer: This channel simplifies complex data science concepts into easy-to-understand lessons, making it ideal for beginners.

4. Networking

Join online communities and forums where you can connect with other data science learners and professionals. These platforms offer opportunities to share knowledge, ask questions, and learn from experienced practitioners:

• Reddit Data Science Community
• LinkedIn Data Science Groups
• Quora Data Science Discussions

FAQs About Data Science Certification Courses

1. What is a Data Science certification?

A Data Science certification is a formal recognition that demonstrates a learner’s knowledge and skills in data science principles, tools, and techniques. Educational institutions or online platforms often award these certifications after completing specific coursework and assessments.

2. Do I need a background in mathematics or statistics to pursue a Data Science certification?

While a background in mathematics or statistics can be beneficial, many certification courses are designed for beginners and provide foundational knowledge. However, having some familiarity with these subjects will help you grasp the concepts more easily.

3. How long does it typically take to complete a Data Science certification course?

The duration of certification courses varies significantly depending on the program structure. Some courses can be completed in a few weeks, while more comprehensive programs may take several months. On average, expect to invest anywhere from 2 to 6 months based on your schedule and course intensity.

4. Are Data Science certifications worth it?

Yes, Data Science certifications can enhance your resume and make you more competitive in the job market. They demonstrate your commitment to learning and can help you gain practical skills that employers seek. Additionally, many organizations recognize reputable certifications as valid qualifications for hiring.

5. What skills will I gain from a Data Science certification course?

Completing a Data Science certification course typically equips you with essential skills, including data manipulation, statistical analysis, machine learning, data visualization, and programming in languages like Python and R. You’ll also gain hands-on experience through real-world projects.

6. Can I take these courses online, or are there in-person options?

Most Data Science certification programs are offered online, providing flexibility to learn at your own pace. Some universities and institutions may also offer in-person classes, but online formats are generally more accessible and convenient for working professionals.

7. Will I receive support during my studies?

Many certification programs provide various forms of support, including access to instructors, mentorship, and peer networking opportunities. Look for programs that offer dedicated support to ensure you have the resources needed for success.

8. What should I consider when choosing a Data Science certification course?

When selecting a certification course, consider factors such as the course content, duration, instructors’ expertise, hands-on projects, industry recognition, and career support services. Also, think about your learning style and schedule to find a program that fits your needs.

Conclusion

If you are still trying to determine which Data Science Certification Online course to enroll in, this list settles it all for you. You only have to pick the one that cares for your training needs and goals. Data Science industry practitioners understand what it takes to become a professional data scientist. This is why they decided to analyze and compile these leading courses. Picking any of these Best Data Science courses will propel you and your career in a big way. The in-depth skills, experience, and ability to help your organization make the right business decisions come with choosing the right course. Beyond these aspects, you’ll also qualify for a great salary package currently at around $127,637 annually, according to Indeed. Start your journey to a successful data science career today, and never look back!