When to comes to data science, you’d think the name explained it all. It’s about the science of data, right?
Wrong.
While yes, data science involves data and science, it also involves so much more. Statistics, mathematics, artificial intelligence, analysis, and visualization all play important roles in the field, and that’s just the tip of the iceberg.
This work doesn’t come cheap either. According to Indeed, data scientists earn on average $119,690 a year, with rates increasing depending on additional qualifications like cloud architecture or DevOps.
If this doesn’t convince you of how wonderfully versatile and vital data science is, then maybe trying it will. Keep reading for access to the best data science courses on the market for beginner and advanced learners. We’ll start by exploring the course content, price, strengths, and weaknesses, then which one is best for you!
What Is Data Science?
So, we know data science is a mixture of many fields, but the goal is always the same. To extract value from data. To do this, you prepare data for analysis, by cleansing, aggregating, and manipulating the data. Then, you use tools to analyze and pull patterns from the results, creating insights and decisions.
Data science goes back as far as 1962 when mathematician John W. Tukey predicted the modern-day electronic computing of data analysis, however, it wasn’t until 2001 when William S. Cleveland advocated for the widespread use of statistical data that the field became what we know today.
Data-based insights, big data, and data analysis are now crucial tools used across most, if not all, industries for multiple jobs like improving efficiency, diagnoses, detecting fraud, and increasing sales.
How to Choose a Data Science Course
When choosing a data science course, you want to choose one with peak teaching methods. We recommend classes with interactive learning, as time and time again, learning by doing has proven to be the most effective way to learn. Plus, it gives you more bang for your buck.
This brings us to our next point, choose a course you can afford! You don’t have to spend hundreds for an amazing course or scrape by with free tutorials. Choose something in between that works for you and your wallet.
Lastly, make sure the content will benefit you. Different classes are geared towards different aspects. For instance, some may cover data science and machine learning, focus on finance, or specific frameworks, among other variations. Choose a class where the outcome aligns with your goals.
Best Beginner Data Science Courses
1. IBM Data Science Professional Certificate – Best Beginner Course
- Skill Level: Beginner
- Pros: Created by tech giant IBM
- Cons: Takes 11 months to complete
IBM is one of the core providers of data science tools, and it’s been in the computer business since 1911, so when there’s an opportunity for an IBM course you take it.
Coursera’s IBM Data Science Professional Certificate is that opportunity. Taught by IBM professionals, this certificate is composed of 10 courses that specialize in data science, machine learning, SQL, Python, and loads more.
The courses are:
- Course 1: What is Data Science?
- Course 2: Tools for Data Science
- Course 3: Data Science Methodology
- Course 4: Python for Data Science, AI & Development
- Course 5: Python Project for Data Science
- Course 6: Databases and SQL for Data Science with Python
- Course 7: Data Analysis with Python
- Course 8: Data Visualization with Python
- Course 9: Machine Learning with Python
- Course 10: Applied Data Science Capstone
Courses 1 and 2 are all about laying down the foundation. You’ll learn about the entire history of data science, starting with the ancient Egyptians, and learn how to use the industry’s most popular tools like Jupyter Notebook, RStudio IDE, GitHub, and IBM Watson Studio.
Course 3 is all about getting you into the mindset of being a data scientist. You’ll learn how to approach data science problems by building problem-solving techniques, collecting and analyzing data, building models, and understanding the feedback after model deployment.
Course 4 teaches you Python, which actually feeds into multiple IBM specializations, and then courses 5 through 9 cover how to use Python for a variety of data science functions. Here you’ll learn SQL, Python libraries like Seaborn, Pandas, and Scikit-Learn, and specifics like ML algorithms, regressions, classification, and how to handle data.
Course 10 caps off this certificate with a capstone project, where you get a taste of real-world data science work using real data sets. Your goal will be to predict if the first stage of the SpaceX Falcon 9 rocket will land successfully using the data science methodology.
This certification comes with a Coursera and an IBM certificate, and costs anywhere between $39 to $89 monthly, depending on your subscription.
This is the best beginner course because it comes with a certification from a global tech name, you learn a whole programming language, get a complete breakdown of data science, and then some with ML and SQL classes. And what’s even better is you can pick which courses you want to take, however, not taking all of them can impede the IBM certification.
2. Udemy’s The Data Science Course 2021: Complete Data Science Bootcamp
- Skill Level: Beginner
- Pros: No experience required
- Cons: Covers a little bit of everything, but not very in-depth
Udemy’s Data Science Course 2021: Complete Data Science Bootcamp is a bestselling course that aims to take beginners to full-fledged data scientists.
Developed by 365 Careers, the number one best-selling provider of business, finance, and data science courses on Udemy, this Bootcamp has helped over 400,000 students. It consists of over 29 hours worth of content split into 63 sections and 476 lectures, all for $59.99. You’ll also get lifetime access and a completion certificate.
You’ll start with some fundamental basics, like what data science is and a breakdown of the entire field. Then move on to specifics like probability, statistics, ML mathematics, deep learning, and advanced statistical methods. You’ll also learn Python, but only the stuff necessary for the course, not the whole language.
Along with lectures, the Bootcamp provides multiple case studies, as well as a TensorFlow appendix for easy navigation. You’ll also get experience using industry-preferred tools like NumPy, Pandas, Matplotlib, Seaborn, Tableau, and Scikit-Learn.
Because of its focus on basics, this course is best for true beginners. We also recommend it for those set on being a data scientist, as everything taught is geared towards that specific career.
3. freeCodeCamp’s Data Science Crash Course – Best Free Data Science Course
- Skill Level: Beginner to Intermediate
- Pros: It’s free!
- Cons: Fast-paced and not as comprehensive as other courses on this list
As the name suggests, freeCodeCamp’s Data Science crash course is a completely free video course taught by data scientist and teacher Marco Peixeiro. All of freeCodeCamp’s video lectures are YouTube integrated, so you can easily access them ad-free there.
The course requires you to know Python, but after that, you’re ready to start setting up your computer for the exercises in the course. You’ll learn must-have basics like linear regression, classification, and resampling and regularization, but also topics like decision trees, SVM, and unsupervised learning.
The video is around 2.5 hours long, but you can work through it at your own pace as some bits will require coding in Python.
This crash course is really for advanced beginners or intermediate programmers that are already comfortable using Python but want to learn how to use it in the data science space. It’s also fast compared to other courses on this list and does not come with a certificate.
For complete courses on Python, check out our article on the best online Python courses
4. Udemy’s Complete Pandas Bootcamp 2021: Data Science with Python – Best Finance Data Science Course
- Skill Level: Intermediate
- Pros: Breakdown of one of the industry best libraries
- Cons: Not for complete beginners
Udemy’s Complete Pandas Bootcamp 2021: Data Science with Python is the ultimate course for Python programmers looking to master the Pandas library, which specializes in data manipulation and analysis.
It’s the highest-rated Pandas course on Udemy, boasting over 15,000 students, and was created by best-selling Udemy instructor Alexander Hagmann. The course contains 34 hours of content in 31 sections and 325 lectures, and it can be all yours – plus lifetime access and a completion certificate – for $59.99.
Along with learning Pandas and DataFrame basics, you’ll learn about data workflows, such as importing and cleaning data, GroupBy operations, and advanced visualization with Seaborn. You’ll also complete data manipulation and aggregation challenges.
This course focuses on general Pandas usage, but also on Pandas for finance and investing and machine learning. There’s even a guide to the new Pandas update.
This is definitely best for professionals who want to reskill into data science by learning a key library or want to drop excel and switch to more powerful data tools. It’s also an ideal course for finance professionals new to data science.
Best Advanced Data Science Courses
5. Udemy’s Python Data Science With Pandas: 12 Advanced Projects
- Skill Level: Advanced
- Pros: Project-Based
- Cons: Focus is on practice not learning new content
Udemy’s Python Data Science with Pandas course picks up where the course above leaves off. It should come as no surprise that this Alex Hagmann original is also a best-selling Udemy course and chock-full of invaluable Pandas insight.
For $59.99, you receive 15.5 hours of lessons divided into 16 sections and 195 lectures, which take place in the form of 12 projects. It does require a working understanding of both Python and Pandas.
Each project gets progressively more advanced, with the first involving a data import of movie data sets and working with APIs and JSON, and the last revolving around data analysis and visualization.
You’ll build machine learning applications, finance applications, learn feature engineering, standardization, dummy variable, web scraping, and sampling. You’ll also learn how to import large data sets with APIs and JSON, as well as work with messy data – real data.
Along with Panadas you’ll get practice using other libraries like Matplotlib, Seaborn, and use SQL databases.
This course is best for working professionals that already use Pandas but are looking to maximize the potential of this powerful library.
6. Coursera’s Advanced Data Science With IBM Specialization – Best Advanced Data Science Course
- Skill Level: Advanced
- Pros: By IBM
- Cons: Large chunk focused on machine learning
Coursera’s Advanced Data Science with IBM Specialization is another IBM original, except this one is only a mere 4 courses, rather than 10. This specialization also requires knowledge of both Python and SQL, and basic mathematics and machine learning.
The courses included are:
- Course 1: Fundamentals of Scalable Data Science
- Course 2: Advanced Machine Learning and Signal Processing
- Course 3: Applied AI with Deep Learning
- Course 4: Advanced Data Science Capstone
Courses 1 teaches you how to describe basic statistical measures, how to identify patterns, trends, and inconsistencies, and how to use useful techniques like dimension reduction and feature selection methods. You’ll use ApacheSpark and Jupyter Notebooks, and other advanced tools to improve big data analysis and create 2D and 3D visualizations.
Course 2 focuses on machine learning used in data science and comes with an IBM digital badge. You’ll learn supervised and unsupervised ML models, linear algebra, and work with Scikit-Learn and SparkML. This course also has a project where you create vibration sensor data using the accelerometer sensors in your smartphone.
Course 3 takes machine learning further with deep learning in data science. You’ll learn about computer vision, deep learning models used in NLP, time series analysis, and neural networks. You’ll also get to use DL frameworks like Keras, TensorFlow, and PyTorch.
Finally, Course 4 offers the final project. For the project, you must prove a deep understanding of data exploration and visualization, advanced machine learning, and how to apply this knowledge in real-world practical use. You also have to prove an understanding of the characteristics of different algorithms and frameworks and how they impact model performance and scalability.
Like the other Coursera program, you can pick and choose which courses to take, omitting some altogether. Depending on the course rate, it costs anywhere between $39 and $89 for a monthly subscription.
This specialization is best for those wanting to expand not only their data science skillset but also their machine learning capabilities. These two fields are very closely intertwined, so this is for professionals looking for the most value out of their data.