Who can learn big data

35 online courses in data science

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Data science is a new digitalization profession with high earnings prospects! We'll show you 35 online courses in data science that will keep you ahead of the curve in this increasingly dynamic, dynamic professional field.

Data science uses methods and techniques from mathematics, statistics, machine learning and programming to Gaining knowledge from data. For companies, insights from data have enormous added value. The ability to identify previously unknown patterns in data sets has also changed many areas of science. This makes the data scientist one of the most sought-after professions.

The job description of the data scientist has only emerged in recent years. Therefore, there has not even been a proper degree in data science. Data science is therefore well suited for career changers.

Nevertheless, there are a few things to consider if you want to assert yourself in this highly competitive professional field.

How do I make a career as a data scientist?

Data science as a profession has only existed for a few years. So until recently there was no formal training in data science. It is therefore generally well suited for career changers. A background in data analysis is not absolutely necessary. Nevertheless, the road to becoming an expert in data science is hard and often long. If you want to train yourself to become a data scientist, you have to be able to motivate and organize yourself well.

Five tips to help you become a data scientist:

  1. Get a solid foundation in programming, statistics, and linear algebra. For example, having a good command of the Python programming language is practically indispensable if you want to get started as a data scientist. You also have to be able to handle algorithms confidently.
  2. Develop advanced skillsin machine learning, pattern recognition, data warehousing and data visualization.
  3. Apply what you have learned to real life examples as early as possible. For example, you could analyze a data collection from the healthcare sector, find out a pattern in the behavior of users on your website, or program your own app. Play around a bit! Applying the skills you have learned to areas for which you are passionate improves your motivation and leads to the fact that you invest the necessary time to become an expert in data science.
  4. Work with professional data scientists. Internships offer an excellent opportunity to do this. The feedback you will receive is essential for your learning progress. Internships also help you to make contacts with potential employers.
  5. Create an online portfolio of your best projects. Creating a portfolio is possibly the most important step in landing your first job in data science.

How can you learn data science?

You can learn data science in a number of ways:

  1. Get a degree in data science from college.
  2. Learn from books. Many textbooks on data science are available free of charge on the Internet. If you understand English well, you may find this list of over 100 free data science textbooks from Learn Data Sci helpful.
  3. Learn data science with the help of online courses. We have more than 200 online courses in data science in our directory. Below is a list of our top 35 online courses in data science. The courses are categorized according to whether they are offered by a university, an IT company or a commercial platform for online courses.

1. Data science online courses from universities

This is a list of online courses offered by universities around the world.

  • UCSD "Data science”- A fee-based beginners' course that teaches the mathematical basics to make business decisions based on data. A certificate is available upon successful completion of the course.
  • Harvard University “Data science”- A paid course for beginners. The curriculum includes machine learning, probability theory, data visualization, linear regression, the R programming language, and more.
  • Johns Hopkins University "Data Science Specialization”- This beginners course gives an introduction to data analysis, data organization, R, machine learning, as well as inductive statistics and the statistical analysis of regression. The course is chargeable.
  • University of Michigan "Data Science Ethics”- The handling of data leads to ethical questions and conflicts. The University of Michigan free online course provides the knowledge and skills students need to reflect and help resolve these ethical issues.
  • UC Berkeley "Foundations of Data Science”- An introduction to programming for data science, machine learning and statistics.
  • Massachusetts Institute of Technology "Statistics and Data Science”- This course assumes an intermediate knowledge of mathematics and Python. It covers probability theory, statistics, machine learning and data analysis. The course is chargeable.
  • University of Washington "Communication Data Science Results”- An advanced course on data visualization and analysis of graphs in the cloud. The course is free and can be completed with a certificate.
  • University of Notre Dame "Data Science Readiness Assessment”- Here participants can test whether their knowledge of arithmetic, linear algebra and programming is sufficient for a career as a data scientist. The assessment itself is free of charge, but a certificate of the test result can be issued for a fee.
  • UC Davis "SQL for Data Science”- The course teaches the basics of SQL and working with data. No background knowledge is required.
  • University of Adelaide "Programming for Data Science”- In this free course for beginners, you will learn how to solve real-life problems using data analysis methods, basic programming and computational thinking.
  • University of Dundee "Data Science in the Games Industry”- This course is about how big data can maximize player experience and profits in the gaming industry.
  • University of Illinois "Master of Computer Science in Data Science”- A rare chance to earn a full Masters degree through MOOCs. To achieve the Masters degree, the student must be enrolled at the University of Illinois. However, the course series can also be viewed free of charge and piece by piece, without the participant having to undertake to complete the entire master's degree.
  • Wesleyan "Data Analysis Tools”- Analysis of Variance, Chi-Square Tests, and Correlation Coefficients are tools that help test hypotheses. In this course you will learn how to use these tools safely.
  • Columbia University "Statistical Thinking for Data Science and Analytics”- This course teaches you how to professionally collect data and develop the right questions to gain relevant insights from raw data.
  • University of Colorado "Data Warehouse Concepts, Design, and Data Integration”- Participants learn to develop data warehouses and integrate data. The audit version of the course is free of charge. A certificate is available for a fee.
  • Purdue University "AP Computer Science A: Java Programming Data Structures and Loops”- The beginners course teaches the basics of the classic programming language Java.
  • University of Virginia "Understanding Your Data Analytical Tools”- You learn which analysis tools are available to you as a data scientist. At the end of the course you will be able to confidently deal with the mediation and moderation of data, as well as with data models and multi-level analyzes.
  • IIT Bombay "Foundations of Data Structures”- Participants acquire a solid basic knowledge of data structures. You will learn how to use simple programming to create and use data structures to appropriately represent, organize, and manipulate data.
  • University of Texas at Arlington "Social Network Analysis”- As a participant in this free course for beginners, you will learn how to analyze social networks with the help of data science. You will understand how people search for and share information in education.
  • Imperial College London "Mathematics for Machine Learning Specialization”- This fee-based course from the renowned Imperial College London teaches the mathematical fundamentals of machine learning and data science applications.
  • Eindhoven University of Technology "Process Mining: Data Science in Action”- Process Mining combines model-based process analysis and data-oriented analysis techniques. Participants acquire skills in Petri Net, Process Modeling, Process Mining and Data Mining.
  • Georgia Institute of Technology "Materials, Data Sciences, and Informatics”- Materials Informatics is a new field of research at the interface between materials science, scientific computing and information science. The course is free and suitable for advanced learners.

In this interview, Dr. Daniel Paurat, how he became a senior data scientist as an autodidact and why online courses are particularly suitable for getting started with data science.


2. Data science online courses from IT companies

This is a list of online courses in data science offered by major IT and software companies:

  • Microsoft “Data Science Essentials”- The free course provides skills in collecting, processing, visualizing data and gaining knowledge from data. Everything is demonstrated using practical examples. Participants learn how to develop a cloud data science solution using the Microsoft Azure machine learning platform, R or Python.
  • IBM "What is data science?”- The beginners course gives an easy-to-understand introduction to data science. It can be completed in just 6 hours.
  • PwC "Data Visualization with Advanced Excel”- In the fee-based course from PricewaterhouseCoopers you learn how to use the built-in functions of Excel to visualize data. The course is of interest to controllers, financial analysts, chief financial officers and auditors.
  • Google Cloud Training "From Data to Insights with Google Cloud Platform Specialization”- This course covers data visualization and data analysis using the Google Cloud Platform.
  • LinkedIn Learning "Data Science Basics: An Introduction”- One of the few courses in German. The methods, tools and techniques of data science are dealt with. Unfortunately there is no certificate option.
  • IEEE "Introduction to Data Storage and Management Technologies”- This fee-free course covers corporate data storage and data management technologies.

 

3. Data Science Online courses from Internet educational platforms

The following is a list of online data science courses offered by private internet platforms:

  • Cognitive Class "Data Science Foundations”- A course suitable for beginners. It covers Python programming, statistics and machine learning. The course costs money. Estimated duration for graduation is 2-4 months.
  • Codecademy "Data Science Path”- A course for beginners that skilfully teaches the basics of machine learning, data visualization, statistical analysis and programming. The course fee is correspondingly high. The course can pay off for beginners and intermediate learners alike.
  • Udacity "Intro to data science”- A free course from Udacity. Although this is a beginner's course, some knowledge of programming and statistics is an asset.
  • Yandex "Big Data for Data Engineers Specialization”- The fee-based course provides an introduction to Hoop, MapReduce, Spark, machine learning and data processing.
  • Udemy "Tableau Ten Advanced Training: Master Tableau in Data Science”- With this course you will become an expert in Tableau 10.
  • Open HPI "Data engineering and data science”- A course in German. The focus is on data collection, data cleansing, data mining, data visualization, machine learning, and big data.

 

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