Data Science is a big deal these days! So it stands to reason that you might want to learn it because of its amazing potential and popularity in the technical market. But you don’t need to spend thousands of dollars on getting a university degree to learn Data Science. It’s even predicted that “armchair data scientists” who don’t have any formal qualifications in Data Science but the skills to analyze data will become even more popular than “traditional data scientists”.
So you can easily learn the basics of Data Science from online courses and then build upon those basics by practice. And luckily for you, there are a lot of online courses on Data Science available! Sites like Coursera, edX, etc. have courses that are created by renowned universities and experts in the field of Data Science. This article demonstrates some of the most popular courses among these. You might need to pay to obtain the official certificates for completing the course but you can access all the course material for free. So let’s check out these courses now!
1. Data Science Specialization by John Hopkins University (Coursera)
This is a Data Science Specialization that will teach you all the concepts and tools you need to know data science from the start to finish. This specialization will help you right from the beginning of the data science pipeline when you need to decide the right questions to ask the data and moving on to inferring the data and then displaying the results using data visualizations. This Data Science Specialization is divided into 10 courses which handle an aspect of data science each namely 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 and the Data Science Capstone Project. The final project will allow you to demonstrate the skills you have learned in real-world situations which will lead to a Certificate of Completion that you can share with your prospective employers.
2. Applied Data Science with Python Specialization by University of Michigan (Coursera)
This Data Science with Python Specialization will introduce you to Data Science through the Python Programming Language. If you have a basic knowledge of Python or even some experience in another programming language, you can use this specialization to apply data science concepts like data visualization, Machine Learning, textual analysis, social network analysis, etc. using Python. It will also introduce you to popular Python toolkits for data science such as pandas, scikit-learn, matplotlib, nltk, networkx, etc. This Data Science with Python Specialization is divided into 5 courses which will provide you knowledge about various aspects of Data Science in Python. These courses include Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python. After completing all five courses you can earn the certificate for this specialization.
3. Applied Data Science Professional Certificate by IBM (Coursera)
This Applied Data Science Professional Certificate will teach you all the skills in Data Science that you need to kickstart your career. This includes open-source tools such as Jupyter, R Studio, Zeppelin notebooks, Watson Studio, and libraries such as Matplotlib, Pandas, NumPy, Seaborn, Scikit-learn, Folium, ipython-sql, ScipPy, etc. In addition to this, you will also learn Python, SQL, data science methodologies, data visualization, data analysis, machine learning, etc. You will use real data science tools and real-world data sets in the IBM cloud to complete the projects in this certificate. There are a total of 9 courses including What is Data Science?, Open Source tools for Data Science, Data Science Methodology, Python for Data Science and AI, Databases and SQL for Data Science, Data Analysis with Python, Data Visualization with Python, Machine Learning with Python, and the Applied Data Science Capstone Project. After completing all these courses, you will obtain a Professional Certificate from Coursera as well as a digital Badge from IBM recognizing your proficiency in Data Science.
4. Professional Certificate in Data Science Fundamentals by Microsoft (edX)
This Professional Certificate in Data Science Fundamentals will provide you with a solid introduction on your path to becoming a data scientist. This is the first stop in the Data Science curriculum provided by Microsoft and it will teach you about working with data and exploring it using various data analytics, visualization, and statistical methods. This certificate will allow you to use Microsoft Excel to explore data and create data models and data visualizations using Excel or Power BI. You will also learn how to apply statistical methods to data and the fundamentals of data storytelling in data analytics. This certificate contains 4 courses namely Analyzing and Visualizing Data with Power BI, Introduction to Data Science, Analytics Storytelling for Impact and Ethics, and Law in Data and Analytics. On completion, you will be provided with an instructor-signed certificate from edX and Microsoft to increase your job prospects.
5. Professional Certificate in Data Science by IBM (edX)
This Professional Certificate in Data Science will provide you with an understanding of the key steps required in managing a data science problem. It will also teach you the tools of the trade including Jupyter Notebooks, RStudio IDE, Watson Studio, etc. You will also learn relational database concepts and SQL to query relational databases. Moreover, this certificate also contains 9 courses along with hands-on labs and projects so that you can apply all the knowledge you learn in the real world. The courses offered are Introduction to Data Science, Data Science Tools, The Data Science Method, SQL for Data Science, Python basics for Data Science, Analyzing data with Python, Visualizing data with Python, Machine Learning with Python, Data Science, and Machine Learning Capstone Project. On completion of the courses, you will be provided with an instructor-signed certificate from edX and IBM to demonstrate your knowledge of Data Science and increase your job prospects.
6. Professional Certificate in Data Science by HarvardX (edX)
This Professional Certificate in Data Science will teach you the fundamentals of Data Science using R. This includes learning R programming skills first and then statistics, probability, data modeling, inference, etc. This certificate will also acquaint you with tidyverse and other specific data science packages such as ggplot2, dplyr, etc. You will also learn Unix/Linux, git, and GitHub, RStudio, and machine learning algorithms that are crucial in Data Science. This certificate also contains 9 courses which are R basics, Visualization, Probability, Inference and Modeling, Productivity tools, Wrangling, Linear Regression, Machine Learning, and the Final Capstone Project. At the end of the Professional Certificate in Data Science, you will be provided with an instructor-signed certificate from edX and HarvardX to demonstrate your knowledge of Data Science with R.
7. Statistics and Data Science MicroMasters by MITx (edX)
The Statistics and Data Science MicroMasters will teach you the foundations of statistics, data science, and machine learning. You will learn how to use the correct probabilistic modeling and statistical inference to extract useful insights from the data. You will also understand the various machine learning algorithms including both supervised and unsupervised methods, clustering methodologies, deep neural networks, etc. This MicroMasters also contains 5 courses which are Probability, Data Analysis in Social Science, Fundamentals of statistics, Machine Learning with Python, and a Capstone Exam in Statistics and Data Science. At the end of this course, you will obtain an instructor-signed certificate from edX and MITx with enough knowledge to make a future career as a Data Scientist, Data Analyst, Data Engineer, Business Intelligence Analyst, Systems Analyst, etc.