The best online courses &  Tutorials to Learn Data Science for beginners to advanced level.

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science.

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. These courses are intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning.

Top Data Science Certification Courses, Tutorials List

  1. IBM Data Science Professional Certificate
  2. Data Science Specialization
  3. Applied Data Science with Python Specialization
  4. Genomic Data Science Specialization
  5. Executive Data Science Specialization
  6. Introduction to Data Science Specialization
  7. Applied Data Science Specialization
  8. Advanced Data Science with IBM Specialization
  9. SQL for Data Science
  10. Data Science with R
  11. Doing Data Science with Python
  12. Data Science A-Z™: Real-Life Data Science Exercises Included
  13. The Data Science Course 2019: Complete Data Science Bootcamp
  14. Learn Python for Data Structures, Algorithms & Interviews
  15. Intro to Data Science: Your Step-by-Step Guide To Starting
  16. Data Science Career Guide - Interview Preparation
  17. Data Science and Machine Learning Bootcamp with R

1. IBM Data Science Professional Certificate

Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.

⭐ : 4.6/5 ( 8,283 ratings)

In this course, you will learn:

  • The major steps involved in tackling a data science problem.
  • The major steps involved in practicing data science
  • Forming a concrete business or research problem
  • Collecting and analyzing data
  • Building a model
  • Understanding the feedback after model deployment

This course is divided into several sections, which covers important topics like Python for data science, databases and SQL for data science, data analysis with Python, data visualization with Python, machine learning with Python, and applied data science capstone.

You'll also learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.

You can take IBM Data Science Professional Certificate on Coursera. The  IBM Data Science Professional Certificate is offered by IBM.

2. Data Science Specialization

Launch Your Career in Data Science. A ten-course introduction to data science, developed and taught by leading professors.

⭐ : 4.5/5 ( 18,722 ratings)

This specialization includes the following courses:

  • 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

In this course, you will learn how to use R to clean, analyze, and visualize data, navigate the entire data science pipeline from data acquisition to publication, use GitHub to manage data science projects, and perform regression analysis, least squares and inference using regression models.

You can take Data Science Specialization on Coursera. The Data Science Specialization is offered by John Hopkins University.

3. Applied Data Science with Python Specialization

Gain new insights into your data . Learn to apply data science methods and techniques, and acquire analysis skills.

⭐ : 4.5/5 ( 10,093 ratings)

This specialization includes five courses, as follows:

  • Introduction 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

This skills-based specialization teaches you how to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, and networks to gain insight into their data.

You will learn how to analyze the connectivity of a social network, conduct an inferential statistical analysis, discern whether a data visualization is good or bad, and enhance a data analysis with applied machine learning.

You can take Applied Data Science with Python Specialization on Coursera. The Applied Data Science with Python Specialization is offered by  University of Michigan.

4. Genomic Data Science Specialization

Become a next generation sequencing data scientist. Master the tools and techniques at the forefront of the sequencing data revolution.

⭐ : 4.5/5 ( 1,532 ratings)

This specialization includes eight courses, as follows:

  • Introduction to Genomic technologies
  • Genomic data science with galaxy
  • Python for genomic data science
  • Algorithms for DNA sequencing
  • Command line tools for Genomic data science
  • Bioconductor for Genomic data science
  • Statistics for genomic data science
  • Genomic data science capstone

This specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, Python, R, Bioconductor, and Galaxy. The sequence is a stand alone introduction to genomic data science or a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics.

You can take Genomic Data Science Specialization on Coursera. The Genomic Data Science Specialization is offered by John Hopkins University.

5. Executive Data Science Specialization

Be The Leader Your Data Team Needs. Learn to lead a data science team that generates first-rate analyses in four courses.

⭐ : 4.5/5 ( 4,769 ratings)

This specialization includes five courses, as follows:

  • A crash course in Data Science
  • Building a data science team
  • Managing data analysis
  • Data science in real life
  • Executive data science capstone

In these four intensive courses, you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.

You can take Executive Data Science Specialization on Coursera. The Executive Data Science Specialization is offered by John Hopkins University.

6. Introduction to Data Science Specialization

Launch your career in Data Science. Data Science skills to prepare for a career or further advanced learning in Data Science.

⭐ : 4.6/5 ( 8,283 ratings)

This specialization includes four courses, as follows:

  • What is Data Science?
  • Open source tools for data science
  • Data science methodology
  • Databases and SQL for data science

In this Specialization you will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science. The specialization entails understanding what is Data Science and the various kinds of activities that a Data Scientist performs. It will familiarize you with various open source tools, like Jupyter notebooks, used by Data Scientists.

It will teach you about methodology involved in tackling data science problems. The specialization also provides knowledge of relational database concepts and the use of SQL to query databases. You will complete hands-on labs and projects to apply their newly acquired skills and knowledge.

You can take Introduction to Data Science Specialization on Coursera. The Introduction to Data Science Specialization is offered by  IBM.

7. Applied Data Science Specialization

Get hands-on skills for a Career in Data Science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning.

⭐ : 4.6/5 ( 3,703 ratings)

This specialization includes four courses, as follows:

  • Python for Data Science
  • Data Analysis with Python
  • Data Visualization with Python
  • Applied Data Science Capstone

In this course, you will learn Python. You will then learn data visualization and data analysis. Through the guided lectures, labs, and projects you’ll get hands-on experience tackling interesting data problems.

You can take Applied Data Science Specialization on Coursera. The Applied Data Science Specialization is offered by IBM.

8. Advanced Data Science with IBM Specialization

Expert in Data Science, Machine Learning and AI. Become an IBM-approved Expert in Data Science, Machine Learning and Artificial Intelligence.

⭐ : 4.3/5 ( 446 ratings)

This specialization includes four courses, as follows:

  • Fundamentals of scalable data science
  • Advanced machine learning and signal processing
  • Applied AI with deep learning
  • Advanced data science capstone

These courses provides you with understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability.

You can take Advanced Data Science with IBM Specialization on Coursera. The Advanced Data Science with IBM Specialization is offered by IBM.

9. SQL for Data Science

This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.).

⭐ : 4.5/5 ( 1,505 ratings)

This course comprises of four modules:

  • Getting Started and Selecting & Retrieving Data with SQL
  • Filtering, Sorting, and Calculating Data with SQL
  • Subqueries and Joins in SQL
  • Modifying and Analyzing Data with SQL

This course starts with the basics and builds on that foundation and gradually have you write both simple and complex queries to help you select data from tables.  You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results.  

You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes.

You can take SQL Data Science on Coursera. The SQL Data Science is offered by IBM.  

10. Data Science with R

Learn how to use the practice of data science and the programming language R to transform your data into actionable insight.

⭐ : 5/5 ( 368 ratings)

In this course, you will learn:

  • About the practice of data science, the R programming language, and how they can be used to transform data into actionable insight
  • How to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical models
  • How to handle Big Data, make predictions using machine learning algorithms, and deploy R to production
  • The skills necessary to use R and the principles of data science to transform your data into actionable insight.

In addition, you'll have built and deployed a web-based interactive machine learning application that allows users to make predictions using data.

You can take Data Science with R on Pluralsight.

11. Doing Data Science with Python

This course shows you how to work on an end-to-end data science project including processing data, building & evaluating machine learning model, and exposing the model as an API in a standardized approach using various Python libraries.

⭐ : 4.5/5 ( 150 ratings)

In this course, you will learn:

  • Various stages of a typical data science project cycle
  • A standardized project template to work on any data science project
  • To use various standard libraries in the Python ecosystem such as Pandas, NumPy, Matplotlib, Scikit-Learn, Pickle, Flask
  • Tackling different stages of a data science project such as extracting data, cleaning and processing data, building and evaluating machine learning model
  • Exposing the machine learning model as APIs
  • A case study that will encompass the whole course to learn end-to-end execution of a data science project

In this course, you will dive into various phases of a data science project such as data extraction, data processing and visualization, building, evaluating, and fine-tuning predictive models, and finally, exposing your predictive models as APIs for real-time integration.

You can take Doing Data Science with Python on Pluralsight.

Data Science Skills in demand

12. Data Science A-Z™: Real-Life Data Science Exercises Included

Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

⭐ : 4.6/5 ( 18,545 ratings)

In this course, you will learn how to:

  • Successfully perform all steps in a complex Data Science project
  • Create Basic Tableau Visualisations
  • Perform Data Mining in Tableau
  • Understand how to apply the Chi-Squared statistical test
  • Apply Ordinary Least Squares method to Create Linear Regressions
  • Read statistical software output for created models
  • Intuitively understand a Logistic Regression
  • Create a Robust Geodemographic Segmentation Model
  • Apply the Cumulative Accuracy Profile (CAP) to assess models
  • Install and navigate SQL Server
  • Use SQL Server Integration Services (SSIS) to upload data into a database
  • Present Data Science projects to stakeholders

This course will teach you how to clean and prepare your data for analysis, how to perform basic visualisation of your data, how to model your data, how to curve-fit your data and finally, how to present your findings and wow the audience.

You can take Data Science A-Z™: Real-Life Data Science Exercises Included on Udemy.

13. The Data Science Course 2019: Complete Data Science Bootcamp

Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

⭐ : 4.5/5 ( 14,973 ratings)

In this course, you will:

  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlow
  • Develop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance

The course provides the entire toolbox you need to become a data scientist. Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, and Deep learning with TensorFlow.

You can take The Data Science Course 2019: Complete Data Science Bootcamp on Udemy.

14. Learn Python for Data Structures, Algorithms & Interviews

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!

⭐ : 4.5/5 ( 41,994 ratings)

In this course, you will learn:

  • How to use Python for Data Science and Machine Learning
  • How to use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • NumPy for Numerical Data
  • Pandas for Data Analysis
  • Matplotlib for Python Plotting
  • Seaborn for statistical plots
  • How to use Plotly for interactive dynamic visualizations
  • How to use SciKit-Learn for Machine Learning Tasks
  • K-Means Clustering
  • Logistic Regression
  • Linear Regression
  • Random Forest and Decision Trees
  • Natural Language Processing and Spam Filters
  • Neural Networks
  • Support Vector Machines

With this course you will learn programming with Python, NumPy with Python, using pandas Data Frames to solve complex tasks, use pandas to handle excel files, web scraping with python, connect Python to SQL, use matplotlib and seaborn for data visualizations, use plotly for interactive visualizations, and machine learning with SciKit.

You can take Learn Python for Data Structures, Algorithms & Interviews on Udemy.

15. Intro to Data Science: Your Step-by-Step Guide To Starting

Learn the critical elements of Data Science, from visualization to databases to Python and more, in just 6 weeks!

⭐ : 4.4/5 ( 633 ratings)

In this course, you will learn:

  • The entire Data Science process
  • Cloud concepts & application in Data Science
  • Database concepts
  • Statistics fundamentals as needed in Data Science
  • Visualizations for data mining and presentation
  • An overview on Statistical Learning
  • The essentials of Machine Learning
  • More advanced Python to apply to Data Science

With this course you’ll discover the structured path for rapidly acquiring Data Science expertise, how to build your ability in statistics to help interpret and analyse data more effectively, how to perform visualizations using one of the industry's most popular tools, and how to apply machine learning algorithms with Python to solve real world problems.

You can take Intro to Data Science: Your Step-by-Step Guide To Starting on Udemy.

16. Data Science Career Guide - Interview Preparation

Prepare for your Data Science Interview with this full guide on a career in Data Science including practice questions!

⭐ : 4.4/5 ( 876 ratings)

With this course, you will be able to:

  • Create a great data science resume
  • Understand various positions and titles available in the data science ecosystem.
  • Get practice with probability and statistics interview questions.
  • Build an understanding of good experiment design.
  • Get practice with SQL interview questions.

You'll start off with an general overview of the field and discuss multiple career paths, including Product Analyst, Data Engineering, Data Scientist, and many more. You'll understand the various opportunities available and the best way to pursue each of them. The course touches upon a wide variety of topics, including questions on probability, statistics, machine learning, product metrics, example data sets, A/B testing, and market analysis.

The course contains real questions with fully detailed explanations and solutions. For questions requiring coded solutions, fully commented code examples will be shown for both Python and R.

You can take Data Science Career Guide - Interview Preparation on Udemy.

17. Data Science and Machine Learning Bootcamp with R

Learn how to use the R programming language for data science and machine learning and data visualization!

⭐ : 4.6/5 ( 7,157 ratings)

In this course, you will learn how to:

  • Program in R
  • Use R for Data Analysis
  • Create Data Visualizations
  • Use R to handle csv, excel, SQL files or web scraping
  • Use R to manipulate data easily
  • Use R for Machine Learning Algorithms
  • Use R for Data Science

This course will teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R. Some of the topics include programming with R, advanced R features, using R data frames to solve complex tasks, use R to handle excel files, web scraping with R, connect R to SQL, use ggplot2 for data visualizations, and se plotly for interactive visualizations Machine Learning with R.

You can take Data Science and Machine Learning Bootcamp with R on Udemy.


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