5 Best Mathematics and Statistics Courses for Data Science and Machine Learning Programmers in 2024
These are the best online courses to learn Mathematics and Statistics skills from Udemy, Coursera, and Pluralsight and become a better Data Scientist in 2024
Hello guys, if you are learning Data Science and Machine learning and looking for some refresher courses to improve your Mathematics and Statistics skills then you have come to the right place.
In the past, I have to share the best data science and machine learning courses, and today, I am going to share the best courses to learn maths and statistics for Data Science. These courses have been created by experts and thought of by top universities. You can join them to improve your Maths skill and become a better data scientist.
One of the main challenges for programmers learning Data Science and Machine learning is the amount of Mathematics involved in it, particularly in deep learning and neural network training.
When I first started exploring deep learning, Maths came as an obstacle. Even though I was an excellent Maths student in my college, I still lag behind in Statistics, Probability, and Calculus involved while learning Data Science, and that’s why I decided to refresh my knowledge and re-learn Statistics and Maths for Data Science.
We also live in a world of Big data, and someone needs to make sense of all this data, and that’s a demand for Data scientists is growing, but it’s not a natural field to jump in. Most of the Data scientists I have met hold a Ph.D. and really good at their Maths and Statistics skills.
Even though you can learn most of Data Science and Machine learning concepts through online courses like Machine Learning by Andrew Ng, which solves the Maths problem for you; and, allow you to entirely focus on deep learning theories; you would still need to refresh your mathematics and statistics concepts which you may have studied before in school or collages.
When you get into a real job solving real problems, not knowing Statistics, Maths, and Probability will not work as an excuse in a real job where you need to come up with your own adaptation to solve the unique problem you have in your hand, and that’s why I suggest you brush your statistics and mathematics skills once you get hold of Machine learning fundamentals.
I have been postponing learning Maths and Statistics for a long time, but last weekend I thought to let’s start and see how it goes. I already had a couple of courses recommended to me by some knowledgeable chaps gone through this path before, and I also had my own shortlisted classes, which I am going to share with you today.
I am still learning, but these are some of the best online courses to learn Statistics and Maths for Data Science based upon recommendations and reviews, and you should definitely check them if you need to brush up on your Maths, Probability, or Statistics skills. It also helps in Data Science interviews; here many interviewers check your grip on these subjects.
Btw, if you're just starting up with Data Science then I suggest you join a more general but comprehensive course like the Data Science A-Z: Real-life Data Science course by Kirill Eremenko on Udemy. This is the best way to start your Data Science journey.
Top 6 Course to learn Statistics and Maths for Data Science in 2024
Without wasting any more of your time, here is my list of some of the best courses to learn Statistics and Mathematics for Data Science and Machine Learning.
1. Statistics for Data Science and Business Analysis
This is one of the best courses to learn the fundamentals of Statistics, not just for Data scientists but for anyone who needs to use statistics for data analysis. In this course, you will learn to efficiently analyze data, formulate hypotheses, and generally reason about what the big set of data is telling you.
The course will also teach you how to plot different types of data and fundamentals like calculating correlation and covariance and calculating measures of central tendency, asymmetry, variability, etc.
You will also learn how to work with different types of data and distributions, understand the mechanics of regression analysis, and learn the concepts needed for data science, even with Python and R.
The animation used in the course really makes it easy to understand complex Statistics and Mathematics concepts like probability.
Here is the link to join this course — Statistics for Data Science and Business Analysis
2. Mathematics for Machine Learning Specialization
For a lot of higher-level courses in Machine Learning and Deep Learning, you will find a need to refresh the basics in mathematics and statistics like probability. These are the concepts you may have studied before in school or university, but which were taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science.
This Specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science.
The Specialization is a collection of 3 courses that will teach you Maths from the Machine learning point of view. You will refresh your knowledge of Linear Algebra and Calculus, along with learning other mathematical concepts that are important in Machine learning.
Here is the link to join this course —Mathematics for Machine Learning Specialization
At the end of this Specialization, you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning and data science.
Like other Coursera specializations, these are free courses if you just want to learn, but you need to pay a subscription fee if you need a certification or wish to do quizzes, assignments, and assessments.
These top Data Science courses are all included in Coursera Plus, an annual subscription that provides access to more than 3,000 courses, Specializations, Professional Certificates, and Guided Projects. If you are planning to take multiple Coursera courses then I highly recommend you join Coursera Plus. You can see here for more details.
3. Become a Probability and Statistics Master
This is one of the most focused courses on Probability and Statistics together. You will learn everything from Probability and Statistics like Data distribution like mean, variance, and standard deviation, normal distributions and z-scores, Data Visualization including bar graphs, pie charts, Venn diagrams, histograms, dot plots, and more.
You will also learn some about analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots and Hypothesis testing like inferential statistics, significance level, type I and II errors, test statistics, and p-values.
Overall, one of the most comprehensive courses to learn Probability and Statistics in a short time. The course contains more than 11 hours of watching material and also comes with 400+ practice questions to test your knowledge.
Here is the link to join this course — Become a Probability and Statistics Master
4. Statistics with R Specialization
This is another awesome resource for Data scientists on Coursera. In this Specialization, you will learn about how to analyze and visualize data in the R programming language and create reproducible data analysis reports.
You will also learn about statistical inference like Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions and, more importantly, communicate statistical results correctly.
If you love the R Programming language and want to be great at data analysis, this course can help you out.
If you are using R for Data Science, then this course is really great for you, but if you are a Python guy like me, there are better choices available.
Here is the link to join this course — Statistics with R Specialization
5. Statistics Foundations: Understanding Probability and Distributions
This is an excellent online course to learn to sample and explore data, as well as basic probability theory and Bayes’ rule. You will examine various types of sampling methods and discuss how such practices can impact the scope of inference.
The course will also teach you many exploratory data analysis techniques like numeric summary statistics and basic data visualization.
You will also learn how to install R and RStudio (free statistical software) and use these tools for Data analysis on lab exercises and a final project. Overall a great course to learn the basics of statistics and probability.
Btw, you would need a Pluralsight membership to get access to this course, which costs around $29 per month or $299 annually (14% discount). It’s more like Netflix for Software Developers, and Since learning is an essential part of our job, Pluralsight membership is a great way to stay ahead of your competition.
They also provide a 10-day free trial without any commitment, which is a great way to not just access this course for free but also to check the quality of courses before joining Pluralsight.
6. Mathematics for Machine Learning and Data Science Specialization by DeepLearning.io
This is a rather new course on Mathematics for Machine Learning and Data Science, created by DeepLearning.io, a company founded by Andrew Ng, a Coursera co-founder and pioneer expert in ML and AI.
The “Mathematics for Machine Learning and Data Science” Specialization, offered by DeepLearning.AI and instructed by Luis Serrano, is a foundational program designed to equip learners with the essential mathematical toolkit required for understanding and implementing machine learning algorithms.
This beginner-friendly specialization covers key mathematical concepts, including calculus, linear algebra, statistics, and probability, providing a comprehensive understanding of the principles that drive machine learning algorithms.
The courses also utilize innovative pedagogy, incorporating easy-to-follow plugins and visualizations, making complex mathematical concepts intuitive and accessible.
Here is the link to join this course — Mathematics for Machine Learning and Data Science Specialization by DeepLearning.io
With a recommended background of at least high school mathematics and basic familiarity with Python, this specialization caters to learners at various levels, I mean even intermediate and experienced developers can also learn few things on this program.
By the end of the program, participants will have acquired the skills to represent data as vectors and matrices, apply vector and matrix algebra operations, understand eigenvalues and eigenvectors, optimize functions in machine learning, and apply statistical methods crucial for data analysis and machine learning model assessment.
With a shareable certificate upon completion, this Specialization serves as a valuable asset for those seeking a deep understanding of the mathematics behind machine learning.
By the way, If you are planning to join multiple Coursera courses or specializations, then consider taking a Coursera Plus subscription which provides you unlimited access to their most popular courses, specialization, professional certificate, and guided projects. It costs around $399/ per year but is worth it because you get access to more than 7000+ courses and projects, and you can also get unlimited certificates.
They are also offering $200 discount now on Coursera Plus annual plan, you can click here to get the discount.
That’s all about some of the best online courses to learn Statistics, Mathematics, and Probability for Data Science and Machine Learning. Good knowledge in these areas goes a long way in analyzing and making sense of Big data you will need to do as part of your job.
A small effort building these foundations or revising it goes a long way to become the successful Data Scientist or Data Engineer you always wanted to be.
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Thanks for reading this article so far. If you like these best Mathematics and Statistics courses, then please share it with your friends and colleagues. If you have any questions or feedback, then please drop a note.
P.S. — If you are keen to learn more about Data Science and Machine Learning and just want to do one thing at this moment, go join the Data Science A-Z: Real-life Data Science course by Kirill Eremenko on Udemy. You won’t regret your decision.
