Are you a **working professional **and looking for the best-advanced data science courses? If yes, then you are in the right place. In this article, you will find the **12** **Best Data Science Courses for Working Professionals**.

To gain data science skills, there are numerous courses available. But I have filtered these courses on the **following criteria-**

**Criteria-**

- Rating of these Courses.
- Coverage of Topics.
- Engaging trainer and Interesting lectures.
- Number of Students Benefitted.
- Good Reviews from various aggregators and forums.

So, without wasting your time, let’s start finding the **Best Data Science Courses for Working Professionals**–

**Best Data Science Courses for Working Professionals**

**Best Data Science Courses for Working Professionals**

- 1. Become a Data Scientist– Udacity
- 2. Applied Data Science with Python Specialization– Coursera
- 3. MicroMasters® Program inData Science– edX
- 4. Data Science Specialization– Coursera
- 5. Python for Data Science and Machine Learning Bootcamp– Udemy
- 6. Data Scientist Masters Program– Edureka
- 7. Advanced Statistics for Data Science Specialization-Coursera
- 8. Data Analysis with R– Udacity
- 9. Statistics with R Specialization– Coursera
- 10. Data Science: Statistics and Machine Learning Specialization– Johns Hopkins University
- 11. Bayesian Statistics: From Concept to Data Analysis– University of California, Santa Cruz
- 12. Practical Statistics– Udacity

**1. Become a Data Scientist– Udacity**

**Rating-** 4.7/5

**Time to Complete-** 4 months( If you spend 10 hrs/week)

This is a **Nano-Degree Program** offered by Udacity. This is an advanced-level program. In this program, you will learn how to solve **Data Science Problems** using **Python Programming,** **Software Engineering Skills**, and **Data Engineering skills**.

The **Udacity Data Science Nanodegree** program is more practical than other courses. The content of this Nanodegree program is **advanced and updated**, combined with **Real-World problems** **created by the leaders in the industry**. Throughout the Nanaodegree program, you will work on the following **4 different projects**–

**Write a Data Science Blog Post****Build Disaster Response Pipelines with Figure Eight****Design a Recommendation Engine with IBM****Data Science Capstone Project**

**Extra Benefits-**

- You will get a chance to work on
**real-world projects with industry experts.** - You will get
**Project feedback from experienced reviewers**. - You will also get
**Technical mentor support.**

**Who Should Enroll?**

Those **who are planning to switch their career to Data Science** and are comfortable with the following concepts-

- Python programming, including common data analysis libraries
**(NumPy, pandas, Matplotlib).** - SQL programming
- Statistics (Descriptive and Inferential)
- Calculus
- Linear Algebra
- Experience wrangling and visualizing data

**Interested to Enroll?**

If yes, then check out the details here- **Become a Data Scientist Program**

**2. ****Applied Data Science with Python Specialization**– Coursera

**Applied Data Science with Python Specialization**– Coursera**Provider- **University of Michigan

**Rating-** 4.5/5

**Time to Complete- **5 months ( 7 hours per week)

This specialization program teaches data science through the **python programming language.** You will get a strong introduction to data science Python libraries, like **matplotlib, pandas, nltk, scikit-learn, and networkx.**

This course series **doesn’t** include **Statistics needed for Data Science** and **Machine Learning algorithms**. It focuses on how to use these algorithms in Python.

If you want to learn Statistics, then first consider the **Statistics with Python Specialization** to learn essential Statistical skills required for data science. This Specialization Program has 5 Courses-

**Courses include-**

**I****ntroduction to Data Science in Python****Applied Plotting, Charting & Data Representation in Python****Applied Machine Learning in Python****Applied Text Mining in Python****Applied Social Network Analysis in Python**

**Extra Benefits-**

- You will earn a
**Shareable Certificate**. - Along with that, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.**

**Who Should Enroll?**

- This program is
**not for Beginners.**This is good for those who have**Intermediate level knowledge**in Data Science. - And those who have
**basic python or programming knowledge.**

**Interested to Enroll?**

If yes, then check out the details here- **Applied Data Science with Python Specialization**

**3. MicroMasters**^{®} Program inData Science– edX

^{®}Program inData Science– edX

**Provider- **UCSanDiego

**Time to Complete- **10 months (9-11 hours per week)

In this program, you will learn the **mathematical and computational tools** that form the basis of data science. You will also learn how to use those tools to make data-driven business recommendations.

This program has two sides to data science learning- **mathematical and applied.**

In the mathematics course, you will learn **probability, statistics, and machine learning**. And in applied, you will get to know about **Python, Numpy, Matplotlib, pandas and Scipy, the Jupyter notebook environment, and Apache Spark**. This program has 4 courses.

**Courses Include-**

**Python for Data Science****Probability & Statistics in Data Science using Python****Machine Learning Fundamentals****Big data analytics using Spark**

**Who Should Enroll?**

- Those who are familiar with
**any programming languages**and have a basic understanding of high-school-level**math.**

**Interested to Enroll?**

If yes, then check out the program details here- **MicroMasters ^{®} Program inData Science**

**4. ****Data Science Specialization**– **Coursera**

**Data Science Specialization**

**Provider-** Johns Hopkins University

**Rating**– 4.5/5

**Time to Complete- **11 months (7 hours per week)

This is also one of the most **highly rated and enrolled course series.** In this course series, there is a separate section on **statistics.** And Knowledge of Statistics is mandatory for Data Science. You will understand the broad directions of **statistical inference** and use this information for making informed choices in analyzing data.

You will also learn **regression analysis** and special cases of the regression model, **ANOVA, and ANCOVA**. Then you will learn** machine learning basics** and how to create a **data product.**

This Data Science specialization Program is the perfect mixture of **theory and practical applications**. R programming language is used for all Data Science related tasks. In this specialization program, there are 10 courses.

**Courses Details-**

**The Data Scientist’s Toolbox****R Programming****Getting and Cleaning Data****Exploratory Data Analysis****Reproducible Research****Statistical Inference****Regression Models****Practical Machine Learning****Developing Data Products****Data Science Capstone**

**Extra Benefits-**

- You will earn
**Shareable Specialization and Course Certificates**. - Along with that, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.**

**Who Should Enroll?**

- Those who have previous working knowledge in any programming language.

**Interested to Enroll?**

If yes, then check out the details here- **Data Science Specialization**

**5. Python for Data Science and Machine Learning Bootcamp– Udemy**

**Rating- **4.6/5

**Time to Complete- **25 hours

This is one of the **best Udemy **courses on Data Science with Python. In this course, you will learn how to **program with Python**, how to create **data visualizations**, and how to use **Machine Learning with Python.** You will also learn about Python libraries such as **NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, etc.**

Along with that, you will learn machine learning algorithms including **Linear Regression, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests, Natural Language Processing, Neural Nets, and Deep Learning, Support Vector Machines, etc.**

**Extra Benefits-**

- You will get a
**Certificate of completion**. - Along with that, you will get
**5 downloadable resources**and**Lifetime access**to the course material.

**Who Should Enroll?**

- Those who have previous programming experience in any language and want to learn Data Science with Python.

**Interested to Enroll?**

If yes, then check here-** Python for Data Science and Machine Learning Bootcamp**

**6. Data Scientist Masters Program– Edureka**

**Provider**– Edureka

**Rating-** 4.4/5

This Data Scientist Masters Program includes training in **Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow, and Tableau**. This Masters’s Program covers almost every topic in Data Science. And it has 12 courses.

**Courses Include-**

- Python Statistics for Data Science Course
- R Statistics for Data Science Course
- Data Science Certification Training
- Python Certification Training for Data Science
- Apache Spark and Scala Certification Training
- AI & Deep Learning with TensorFlow
- Tableau Training & Certification
- Data Science Master Program Capstone Project

Along with that, there are some **FREE** Elective Courses-

- SQL Essentials Training & Certification
- R Programming Certification Training
- Python Programming Certification Training
- Scala Essentials
- MongoDB® Training And Certification

**Extra Benefits-**

- You will get a
**Masters’s Course Certification**. - You will get lifetime access to
**presentations, quizzes, and installation guides.** - Along with that, you will get a
**Personal Learning Manager**who will answer all your queries.

**Who Should Enroll?**

- Anyone can enroll, whether you are an
**experienced professional, working in the IT industry,**or an aspirant planning to enter the world of Data scientists.

**Interested to Enroll?**

If yes, then check it out here- **Data Scientist Masters Program**

**7. Advanced Statistics for Data Science Specialization-Coursera**

**Rating- **4.5/5

**P****rovider-** Johns Hopkins University

**Time to Complete- **5 months( If you spend 2 hrs/week)

This is an **advanced-level specialization program **for data science. In this program, you will learn the advanced concepts of statistics and understand the **behind-the-scenes mechanism** of **key modeling tools in data science**, like **least squares and linear regression.**

In this course, you will get a firm foundation in the **linear algebraic treatment of regression modeling**, which will greatly augment applied data scientists’ general understanding of regression models. There are 4 Courses in this Specialization.

**Courses Details-**

**Mathematical Biostatistics Boot Camp 1****Mathematical Biostatistics Boot Camp 2****Advanced Linear Models for Data Science 1: Least Squares****Advanced Linear Models for Data Science 2: Statistical Linear Models**

**Extra Benefits-**

- You will earn
**Shareable Specialization and Course Certificates**. - Along with that, you will get
**Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.**

**Who Should Enroll?**

- Those who have previous knowledge in basic calculus and linear algebra.

**Interested to Enroll?**

If yes, then check out the details here- **Advanced Statistics for Data Science Specialization**

**8. ****Data Analysis with R– Udacity**

**Data Analysis with R– Udacity**

**Time to Complete- **2 Months

This is a **completely FREE** course to learn **data analysis using R programming**. This course begins with the introduction of **exploratory data analysis (EDA).** Then you will learn R basics by installing RStudio and packages.

After that, you will perform EDA to understand the **distribution of a variable** and to check for **anomalies and outliers**. You will also learn how to **quantify and visualize individual variables **within a data set to make sense of a **pseudo-data set of Facebook users.**

In this course, you will work on the **Diamonds and Price Predictions** project. In this project, you will investigate the diamond data set and see how predictive modeling can allow us to determine a good price for a diamond.

**Who Should Enroll?**

- Those who have prior knowledge of statistics.

**Interested to Enroll?**

If yes, then check out the course details here- **Data Analysis with R**

**9. Statistics with R Specialization– Coursera**

**Rating-** 4.6/5

**Provider-** Duke University

**Time to Complete- **7 Months (If you spend 3 hours/week)

This specialization program will give you **in-depth Statistics knowledge** with the help of **R**. In this program, you will learn how to **analyze and visualize data in R** and create reproducible data analysis reports, and much more.

R is much better than Python for performing statistical operations. So, if you want to master Statistics, then I would recommend this specialization program.

In this specialization program, you will learn the following skills- **Bayesian Statistics, Linear Regression, Statistical Inference, R Programming, Statistics, Rstudio, Exploratory Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Bayesian Linear Regression, Bayesian Inference, and Model Selection.**

This specialization program contains **5 Courses**. Let’s see the courses details-

**Courses Include-**

**Introduction to Probability and Data with R****Inferential Statistics****Linear Regression and Modeling****Bayesian Statistics****Statistics with R Capstone**

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with this, you will get

**Who Should Enroll?**

- Those who have
**basic math knowledge**. No previous programming knowledge is required for this course.

**Interested to Enroll?**

If yes, then check out all details here- **Statistics with R Specialization**

**10. Data Science: Statistics and Machine Learning Specialization– ****Johns Hopkins University**

**Johns Hopkins University****Rating- **4.6/5

**Time to Complete-** 6 months (If you spend 6 hours/week)

This is another Specialization program dedicated to **statistics** concepts. In this program, you will learn **statistical inference, regression models, machine learning, and the development of data products.**

At the end of this program, you will work on **Capstone Project**, where you will apply the skills learned by building a data product using real-world data. This specialization program uses the **R programming language.**

There are 5 courses in this specialization program.

**Extra Benefits-**

- You will get a
**Shareable Certificate and Course Certificates**upon completion. - Along with that, you will get

**You Should Enroll if-**

- You have a good understanding of R programming.

**Interested to Enroll?**

If yes, then check out all details here- **Data Science: Statistics and Machine Learning Specialization**

**11.** **Bayesian Statistics: From Concept to Data Analysis– ***University of California, Santa Cruz*

*University of California, Santa Cruz*

**Rating- **4.6/5

**Time to Complete- **12 hours

This is another **Free to Audit **course for statistics. This course begins with the **basics of probability and Bayes’ theorem**. Then covers the **concepts of statistical inference from both frequentist and Bayesian perspectives.**

After that, you will learn **methods for selecting prior distributions and building models for discrete data**. And in the last, this course covers the **conjugate and objective Bayesian analysis for continuous data.**

**You Should Enroll if-**

- You have prior knowledge of basic statistics class (for example, probability, the Central Limit Theorem, confidence intervals, linear regression) and calculus (integration and differentiation).

**Interested to Enroll?**

If yes, then start learning- **Bayesian Statistics: From Concept to Data Analysis**

**12. Practical Statistics– Udacity**

**Rating- **NA

**Provider- **Mode

As the name sounds, “**Practical Statistics**“, this course is focused on the** practical implementation** of statistical concepts. In this course, you will understand how to tackle common real-world challenges, such as **analyzing AB tests **and building **regression models.**

In this course, there is a **project**, where you have to use **statistical techniques **to answer questions about the data and report your conclusions and recommendations in a report. Dataset will be provided.

Topics covered in this course are- **Simpson’s Paradox, Probability, Binomial Distribution, Conditional Probability, Bayes Rule, Standardizing, Sampling Distributions, and Central Limit Theorem, confidence intervals, Hypothesis Testing, T-Tests, and A/B Tests, Regression, multiple linear regression, and logistic regression.**

**Extra Benefits-**

- You will chance to work on
**real-world projects with industry experts.** - You will get
**Project feedback from experienced reviewers**. - You will also get
**Technical mentor support.**

**Who Should Enroll?**

- Those who have experience working with
**SQL**and with data in**Python.**

**Interested to Enroll?**

If yes, then check out all details here- **Practical Statistics**

And here the list ends. I hope these **Best Data Science Courses for Working Professionals** will definitely help you. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

**Conclusion**

In this article, I tried to cover the **12 Best Data Science Courses for Working Professionals**. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

**FAQ**

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