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The 7 Best Data Science Courses That Are Worth Taking In 2024
A career in data science involves using statistical, computational and analytical methods to extract insights from data. Data scientists regularly use programming languages like Python and R alongside machine-learning algorithms and data-visualisation software.
The need for data scientists has surged across various sectors, including finance, healthcare and technology, making it a highly sought after and lucrative profession. According to the U.S. Bureau of Labor Statistics, the average annual salary for data scientists in 2023 was $108,020, while demand for them is expected to increase by 35% in the next eight years — much faster than average for all occupations.
SEE: What is Data Science? Benefits, Techniques and Use Cases
Online courses and certifications provide accessible pathways into the field, as many can fit around existing responsibilities like a day job. Such programs provide the expertise required for an individual to land their first data science role or just discover whether the career is for them. TechRepublic takes a look at the top six data science courses available in 2024 for learners with different goals and levels of experience.
SEE: How to Become a Data Scientist: A Cheat Sheet
Best data science courses: Comparison table IBM Data Science Professional Certificate - Coursera: Best for a data science overview
The IBM course is idea; for beginners seeking a thorough, self-paced introduction to data science. Image: Coursera/Screenshot by TechRepublic
The Data Science Professional Certificate from IBM, hosted on Coursera, offers a great starting point for those interested in learning about data science but don't fully understand what a career in it would entail. This course provides an overview of the tools, languages and libraries used daily by professional data scientists and puts them into practice through a number of exercises and projects. The final Capstone project also requires the student to create a GitHub account, encouraging them to familiarise themselves with the site and collaborate.
Price$49/£38 per month after a seven-day free trial.
DurationSix months at ten hours a week.
ProsNone.
Associate Data Scientist in Python - DataCamp: Best for beginner Python skills
The DataCamp course provides practical, tool-focused coding skills for data science beginners. Image: DataCamp/Screenshot by TechRepublic
DataCamp is another well-regarded provider of data-related courses, and one of its highest rated is titled 'Associate Data Scientist in Python'. It sets itself apart with its unique hands-on coding exercises, one of which involves manipulating and visualising data on Netflix movies. Language-wise, this course exclusively uses Python, but introduces learners to multiple libraries including pandas, Seaborn, Matplotlib and scikit-learn. Knowledge of Python is not required for this course, as the necessary skills are taught along the way.
Price$13/£11 a month for full access.
DurationNine weeks at ten hours a week.
Pros ConsNone.
R Programming A-Z - R For Data Science With Real Exercises! - Udemy: Best for beginner R skills
Udemy's 'R Programming A-Z' teaches the fundamentals of the R language in a data science context. Image: Udemy/Screenshot by TechRepublic
While many data science courses are taught with Python due to its popularity and simplicity, 'R Programming A-Z' on Udemy is aimed at learners looking to get to grips with R and RStudio. R is a powerful language used frequently in data science for handling complex data sets. This course assumes no prior knowledge and starts with the very basics of R programming, including variables and for() loops, before looking at matrices, vectors and more advanced data manipulation. Large projects that help cement learning use real-world financial and sports data.
Price$109.99/£69.99.
Duration10.5 hours of lectures + exercises.
ProsNone.
Applied Data Science Specialization - Coursera: Best for beginner applications
This course teaches real-world applications of data science at a beginner level. Image: Coursera/Screenshot by TechRepublic
"Applied Data Science Specialization," another course by IBM, fast tracks data science beginners towards skills with real-life applications. Python skills for data analysis and visualisation are taught assuming no prior knowledge of the language and are then put into practice in the interactive labs and projects. These cover the extraction and graphing of financial data, creation of regression models to predict housing prices and visualisation of data treemaps and line plots on Python dashboards. By the end of the course, participants should have solidified their practical Python skills to the extent that they can confidently explore more advanced topics like big data, AI and deep learning.
Price$49/£38 per month after a seven day free trial.
DurationTwo months at ten hours a week.
ProsNone.
Mathematics for Machine Learning and Data Science Specialization - Coursera: Best for mathematics for data science
The course provides a foundation in essential mathematical concepts tailored for ML and data science applications. Image: Coursera/Screenshot by TechRepublic
As the title suggests, this course from DeepLearning.Ai has a particular focus on mathematics for data scientists. Mathematics underpins the profession and is essential for understanding algorithms, cleaning data, drawing insights, visualisation, evaluating models and more. The course covers the fundamental mathematical toolkit of machine learning, including calculus, linear algebra, statistics and probability. Learners say it provides a good entry point into the theory of data science and the lab exercises are practical.
Price$49/£38 per month after a seven-day free trial.
DurationSix weeks at ten hours a week.
ProsA high school level of mathematics and a basic knowledge of Python is recommended.
MITX - Statistics and Data Science with Python - edX: Best for college graduates
The year-long MicroMasters offers a deep dive into probability, statistical inference, machine learning and data analysis. Image: edX/Screenshot by TechRepublic
The "Statistics and Data Science with Python" course presented by the Massachusetts Institute of Technology is by far the most comprehensive course featured on this list. The so-called "MicroMasters" takes learners over 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 practical experience building machine learning algorithms. It is designed to fit around a day job or university study while not compromising on the level of content.
Price$1,350/£1,186.
DurationOne year and two months at ten hours a week.
ProsUniversity-level calculus and comfort with mathematical reasoning and Python programming 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 primarily looks to interpret existing data, while the latter involves creating new ways of doing so.
Data analysis focuses on examining datasets to identify trends, draw conclusions and support business decisions. It involves cleaning, transforming and modelling data to extract useful information, often using tools like Excel and SQL. It is performed by data analysts who are typically hired into a wide range of industries, including marketing firms, government agencies, healthcare providers, financial institutions and more.
Data science, on the other hand, integrates data analysis with advanced machine learning algorithms, predictive modelling and big data technologies. Data scientists often develop new tools and methods to handle complex problems and derive insights from large-scale datasets. Skills required for this include proficiency in programming languages such as Python and R, as well as a deeper understanding of statistical methods and machine learning.
SEE: 10 Signs You May Not Be Cut Out for a Data Scientist Job
Is data science still in demand in 2024?Data science remains in high demand in 2024. The IDC estimates that the amount of data worldwide will reach 291 zettabytes by 2027, and as growth continues, more data professionals will be needed to manipulate and interpret it. Furthermore, many of the key industries within which data scientists work are expanding, such as AI, 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 as, according to Glassdoor, the average base pay of a data scientist in the U.S. Is $113,000.
Are data science courses worth it?Opinions on online data science courses vary within the industry. For some, there are enough free resources available through platforms like YouTube to render paid courses unnecessary. They may also argue that there is no substitute for hands-on experience, and that even beginners should learn the necessary skills by downloading an open-source dataset and attempting to manipulate it themselves.
However, the key to learning anything new is persistence, and it can be difficult to remain motivated without a defined learning programme to follow, coursemates to connect with or a course fee at risk of going to waste. For individuals with a tendency to start projects but not finish them, an initial investment in a structured course may provide the motivation they need. Many paid courses also give direct access to qualified instructors who can provide tailored help that would otherwise not be available.
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 desire, then the investment may be worth it.
MethodologyWhen assessing online courses, TechRepublic examined the reliability and popularity of the provider, the depth and variety of topics offered, the practicality of the information, the cost and the duration. The courses and certification programs vary considerably, so be sure to choose the option that is right for your goals and learning style.
Who Is Learning Gen. AI Right Now? Coursera CEO Explains
75% of professionals are using some form of AI, according to data from Microsoft (MSFT), while more employers are seeking out workers with artificial intelligence experience. How can future employees learn to utilize AI and where can they find these upskilling opportunities?
Coursera (COUR) CEO Jeff Maggioncalda joins Wealth! To give insight into the online course provider's current curriculum for AI education that could give a boost to workers' skill sets, commenting on the demographics and industries utilizing these courses the most.
"What we're seeing is interesting in the US, there are more women taking courses on Coursera. But when you look at enrollments in generative AI courses, it's 70% men, 30% women. So it's definitely skewing more to men right now, which is a little bit troubling in the sense that many studies have shown that those types of jobs most likely going to be impacted by generative AI, those dealing with language and sound and video often are held by women employees.
"Millennials are accounting for over 50% of the enrollments in generative AI, then followed by Gen Z, and then Boomers, and then in terms of geography, Texas and India. Seems like everybody in Texas and India wants to learn generative AI," Maggioncalda explains
For more expert insight and the latest market action, click here to watch this full episode of Wealth!
This post was written by Nicholas Jacobino
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Top AI Learning Platforms For Preparing Students For Tomorrow
As the world is evolving into the digital era, education and learning become one of the most essential aspects of the digital revolution as not only it in itself is evolving but this field is the one that trains and prepares people to accept the changes in all other sectors. One such sector that is evolving rapidly is Artificial Intelligence (AI). From Metaverse to Chatbots, everyone has welcomed AI with open hands. Therefore it has become a necessity to equip students with expertise in AI education to thrive in an evolving technological landscape and develop skills in the field.
Here are a few platforms that utilise various means to provide learning experiences to every child who wishes to make a career in AI and Technology development.
1. Yuvipep
YuviPep is a leading AI learner platform built on an interactive and practical understanding that connects theory to real-world application through hands-on training methods. Through incorporating practical projects and simulations, YuviPep ensures students understand AI-related theories while equipping them with skills for applying those same theories in real life, thereby giving them a deep understanding and preparedness for the challenges of tomorrow. Also, ensuring they are well-prepared to tackle complex challenges in AI development and implementation. With a commitment to bridging the gap between academic learning and industry demands, YuviPep equips learners with the expertise and credentials needed to succeed in diverse AI career paths.
2. EdX: edX is the online learning platform from world-leading digital education company 2U, Inc. EdX was founded by Harvard and MIT as an experiment to make the world's best education available to everyone.
It provides worldwide online learning that delivers real professional progress across nearly every career discipline, from artificial intelligence and robotics to sustainability and public health.
3. Coursera
Coursera has established itself as a cornerstone in AI education by offering a versatile platform that accommodates a wide range of learning preferences and goals. Whether students prefer self-paced study for flexibility or structured courses with rigorous certifications upon completion, Coursera provides options that cater to diverse learning needs. This flexibility not only allows learners to customize their learning experience but also ensures that they receive recognition for their achievements in AI proficiency, making Coursera a preferred choice for those looking to advance their careers or deepen their understanding of artificial intelligence. By partnering with top universities and industry experts, Coursera maintains its commitment to delivering high-quality content that remains relevant and up-to-date with the latest advancements in AI technology, thereby empowering students worldwide to succeed in this rapidly evolving field.
4. Tinkerly
Tinkerly pioneers an innovative approach in AI learning courses to prepare students for the future by integrating STEM educational kits into interactive online coding classes. Our mission is to make STEM education engaging and accessible from an early age through personalized learning experiences. Using a blend of hands-on activities and advanced technology, we introduce Robotics, IoT, and AI concepts, allowing students to not only learn coding but also gain practical skills in product innovation. Serving both government and private schools, we offer Tinkering Labs, Coding Classes, STEM kits, and the Let's Tinker Mobile App to foster comprehensive educational development.
5. Stempedia
Stempedia stands out among innovative platforms focused on AI learning courses, dedicated to preparing students for the future. By integrating advanced AI technologies into their curriculum, Stempedia offers a cutting-edge approach to education. Their focus on tangible and practical lessons with robotics, IoT, and applications of AI prepares the students for the modern world not only in technical aspects but also enhances the creativity and thinking skills of the students. This approach is suitable for developing learners' practical experiences in the new technologies available in the present market to increase their employability in a future dynamic world.
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