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Data science careers involve using statistical, computational, and analytical methods to extract insights from data. Data scientists often use programming languages such as Python and R, as well as machine learning algorithms and data visualization software.
The surge in demand for data scientists in various fields such as finance, healthcare and technology has made it a highly sought-after and lucrative profession. U.S. Bureau of Labor Statisticsthe average annual salary for data scientists will be $108,020 in 2023, and demand for them is expected to grow 35% over the next eight years—much faster than the average for all occupations.
look: What is Data Science? Benefits, Technologies, and Use Cases
Online courses and certifications offer an easy way to enter the field, as many can be combined with existing responsibilities, such as a day job. Such courses provide individuals with the expertise they need to land their first data science position, or simply discover if this career is right for them. TechRepublic lists the top six data science courses for 2024 for learners with different goals and experience levels.
look: How to Become a Data Scientist: A Cheat Sheet
Best Data Science Courses: Comparison Chart
IBM Professional Certificate in Data Science – Coursera: Best for Data Science Overview
IBM’s Data Science Professional Certificate program on Coursera provides a great starting point for those who are interested in learning data science but don’t fully understand what a data science career might look like. The course provides an overview of the tools, languages, and libraries that professional data scientists use every day and puts them into practice through a series of exercises and projects. The final Capstone project also requires students to create a GitHub account, encouraging them to become familiar with the site and collaborate.
price
After a seven-day free trial, it costs $49/£38 per month.
period
Ten hours a week for six months.
advantage
- Industry-recognized and backed by IBM.
- Self-paced.
shortcoming
- Lacks depth as it aims to provide only the basics of theoretical data science and practical applications.
prerequisites
not any.
Python Assistant Data Scientist – DataCamp: Best for Python Beginners
DataCamp is another well-respected provider of data-related courses, and one of its top-rated courses is “Python Assistant Data Scientist.” It stands out for its unique hands-on coding exercises, one of which involves manipulating and visualizing data from Netflix movies. Language-wise, this course uses only Python, but introduces learners to multiple libraries, including pandas, Seaborn, Matplotlib, and scikit-learn. This course does not require Python knowledge, as the necessary skills are taught during the course.
price
Get full access for $13/£11 per month.
period
Ten hours per week for nine weeks.
advantage
shortcoming
- Insufficient understanding of theoretical elements of data science.
- Python-specific knowledge may not translate to different environments.
prerequisites
not any.
R Programming A-Z – R Data Science with Real Practice! – Udemy: Best R Skills for Beginners
While many data science courses are taught in Python due to its popularity and ease of use, the “R Programming A-Z” course on Udemy is for learners who want to master R and RStudio. R is a powerful language that is frequently used in data science to work with complex data sets. This course requires no prior knowledge and starts with the basics of R programming, including variables and for() loops, before moving on to matrices, vectors, and more advanced data operations. Large projects that help consolidate learning use real-world financial and sports data.
price
$109.99 / £69.99.
period
10.5 hours of lectures + exercises.
advantage
- Specific to R and RStudio.
- The steep learning curve typically associated with R is eliminated.
- Self-paced.
shortcoming
- Relatively little attention has been paid to data science and machine learning.
- Tutorials on a Mac and instructions for Windows devices aren’t always clear.
prerequisites
not any.
Applied Data Science Specialization – Coursera: Best for beginners
Another course from IBM, the Applied Data Science Specialization, is designed to quickly get data science beginners up to speed with real-world application skills. The data analysis and visualization Python skills taught in the course assume no prior knowledge of the language, and then apply those skills in interactive labs and projects. These skills include extracting and plotting financial data, creating regression models to predict house prices, and visualizing data treemaps and line graphs on Python dashboards. By the end of the course, participants should have solidified their practical Python skills and be able to confidently explore more advanced topics such as big data, artificial intelligence, and deep learning.
price
$49/£38 per month after a seven-day free trial.
period
Ten hours a week for two months.
advantage
- Suitable for beginners.
- Help learners quickly master the practical applications of data science.
- Self-paced.
shortcoming
- Lack of basic knowledge provided.
prerequisites
not any.
Mathematics for Machine Learning and Data Science Specialization – Coursera: Best for Mathematics for Data Science
As the title suggests, this course from DeepLearning.ai places a strong emphasis on math for data scientists. Math is fundamental to a career as a data scientist and is essential for understanding algorithms, cleaning data, gaining insights, visualization, evaluating models, and more. The course covers the basic math toolkit for machine learning, including calculus, linear algebra, statistics, and probability. Learners say the course provides a great entry point into data science theory, and the lab exercises are also very practical.
price
After a seven-day free trial, it costs $49/£38 per month.
period
Ten hours per week for six weeks.
advantage
- Self-paced.
- Covers mathematics relevant to applied data science.
shortcoming
- Not every topic is explored in depth.
prerequisites
High school math and basic knowledge of Python are recommended.
MITX – Statistics and Data Science with Python – edX: Best for College Graduates
The Statistics and Data Science with Python course offered by MIT is by far the most comprehensive course on this list. The so-called “micromasters” takes learners more than a year to complete and prepares them for their first career in data science. It provides a graduate-level introduction to concepts such as statistical inference and linear models, as well as hands-on experience building machine learning algorithms. It is designed to fit into everyday work or university studies without compromising on the level of content.
price
$1,350 / £1,186.
period
Ten hours a week, one year and two months.
advantage
- Comprehensive.
- Prepare learners for data science jobs.
shortcoming
- It requires a lot of time investment.
- cost.
- Requires advanced mathematical knowledge.
prerequisites
College-level calculus knowledge and mathematical reasoning as well as Python programming skills are recommended.
What is the difference between data analysis and data science?
The key difference between data analysis and data science is that the former focuses primarily on interpreting existing data, while the latter involves creating new methods.
Data analysis focuses on examining data sets to identify trends, draw conclusions, and support business decisions. It involves cleaning, transforming, and modeling data to extract useful information, typically using tools such as Excel and SQL. It is performed by data analysts, who are typically employed by a variety of industries, including marketing companies, government agencies, healthcare providers, financial institutions, and more.
Data science, on the other hand, combines data analysis with advanced machine learning algorithms, predictive models, and big data techniques. Data scientists often develop new tools and methods to tackle complex problems and gain insights from large-scale data sets. This requires skills such as proficiency in programming languages such as Python and R, as well as a deeper understanding of statistical methods and machine learning.
look: 10 Signs You Might Not Be a Data Scientist
Will Data Science Still Be in Demand in 2024?
In 2024, data science will remain in high demand. IDC estimates that the amount of data in the world will Will reach 291 ZB As growth continues through 2027, more data professionals will be needed to process and interpret data. Additionally, many key industries where data scientists work are expanding, such as artificial intelligence, machine learning, and the Internet of Things, while others provide core services such as healthcare, energy, finance, and logistics. Salaries also reflect this high demand, according to Glass doorthe average base salary for data scientists in the United States is $113,000.
Are Data Science Courses Worth It?
Opinions on online data science courses vary among industry professionals. Some believe that there are enough free resources on platforms such as YouTube that there is no need to purchase paid courses. They may also believe that there is no substitute for practical experience and that even beginners should learn the necessary skills by downloading open source datasets and trying to operate on their own.
However, the key to learning anything new is perseverance, and it can be difficult to stay motivated without a clear study plan, classmates to connect with, and tuition money to waste. For those who tend to start projects but often fail to finish them, the initial investment in a structured course may provide the motivation they need. Many paid courses also provide direct access to qualified instructors who can provide customized help that would otherwise be unavailable.
Ultimately, there are certainly opportunities to break into data science without taking any type of online course. However, if structured learning provides the skills or motivation you want, the investment may be worth it.
method
When evaluating online courses, TechRepublic looked at the provider’s reliability and popularity, the depth and variety of topics offered, the usefulness of the information, cost and duration. Courses and certification programs vary widely, so be sure to choose an option that fits your goals and learning style.
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