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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## Though of the Day…

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‘It’s what you learn after you know it all that counts.’John Wooden

### Written By Aqsa Zafar

Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.