Best Online Data Science Courses with Certifications
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To learn Data Science, however, you don’t have to spend thousands of dollars on a college education.
It is even anticipated that “armchair data scientists,” who lack formal training in data science but possess the abilities to interpret data, would surpass “traditional data scientists” in popularity.
So it is simple to acquire the fundamentals of data science through online classes, and you can then improve on those fundamentals through practice. And fortunately for you, there are lots of online Data Science courses accessible! Courses on websites like Coursera, edX, etc. were developed by famous universities and data science professionals.
Some of the most well-liked courses among them are illustrated in this article. The formal certificates for passing the course may require payment, however you can view all of the course materials without paying a dime. So let’s look at these courses right away!
1. John Hopkins University’s Data Science Specialization (Coursera)
This data science specialization will provide you with the knowledge and resources you need to understand data science from beginning to end.
When you need to choose the appropriate questions to pose to the data, move on to inferring the data, and finally present the findings using data visualizations, this specialization will be of assistance to you at every stage of the data science pipeline.
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 are the 10 courses that make up this Data Science Specialization, each of which focuses on a different aspect of data science.
Your final project will provide you the chance to apply the knowledge you have gained in practical settings, and it will result in a Certificate of Completion that you can show potential employers.
2. The University of Michigan’s Applied Data Science with Python Specialization (Coursera)
Through the Python programming language, this Data Science with Python Specialization will expose you to data science. You can use this specialization to apply Python to data science topics like data visualization, machine learning, textual analysis, social network analysis, etc. if you have a basic understanding of Python or even some expertise with another programming language.
Additionally, it will teach you to well-known Python data science toolkits as pandas, scikit-learn, matplotlib, nltk, networkx, etc. The five courses that make up this Data Science with Python Specialization will teach you about different facets of Data Science in Python.
The following courses are among them: Introduction to Data Science in Python; Applied Plotting, Charting & Data Representation; Applied Machine Learning; Applied Text Mining; and Applied Social Network Analysis.
You can obtain the specialization’s certificate after finishing all five courses.
3. IBM (Coursera) Applied Data Science Professional Certificate
You will learn all the data science skills required to launch your career in this Applied Data Science Professional Certificate program.
Along with libraries like Matplotlib, Pandas, NumPy, Seaborn, Scikit-learn, Folium, ipython-sql, ScipPy, and others, this also contains open-source tools like Jupyter, R Studio, Zeppelin notebooks, Watson Studio, etc.
You will also learn Python, SQL, data science approaches, data visualization, data analysis, machine learning, etc. in addition to the aforementioned.
To complete the projects for this degree, you will utilize real data science tools and real-world data sets in the IBM cloud.
Nine different courses are offered, 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.
You will receive a Professional Certificate from Coursera and a digital Badge from IBM, both of which recognize your skill in data science, after finishing all of these courses.
4. Microsoft’s Professional Certificate in Data Science Foundations (edX)
On your journey to become a data scientist, this Professional Certificate in Data Science Fundamentals will serve as a strong starting point.
This is the first lesson in Microsoft’s Data Science curriculum, which teaches you how to interact with data and explore it using a variety of data analytics, visualization, and statistical techniques.
With the aid of Microsoft Excel and Power BI, you will be able to study data, build data models, and visualize it.
Additionally, you will master the principles of data storytelling and how to apply statistical methodologies to data in data analytics.
Analyzing and Visualizing Data with Power BI, Introduction to Data Science, Analytics Storytelling for Impact and Ethics, and Law in Data and Analytics are the four courses that make up this credential. When finished, you will receive a certificate from edX and Microsoft that has been signed by the teacher to improve your career prospects.
5. IBM (edX) Professional Certificate in Data Science
With the help of this Professional Certificate in Data Science, you will be able to manage a data science problem by knowing the essential procedures that must be taken.
It will also show you how to use the necessary tools, such as RStudio IDE, Watson Studio, and Jupyter Notebooks.
Additionally, you’ll learn relational database concepts and SQL for querying them. Additionally, this credential includes 9 courses with practical labs and projects so that you can put all of the knowledge you learn to use.
Data Science Tools, The Data Science Method, SQL for Data Science, Python fundamentals for Data Science, Analyzing data with Python, Visualizing data with Python, Machine Learning with Python, Data Science, and Machine Learning Capstone Project are the courses that are available.
You will receive a certificate from edX and IBM with the instructor’s signature after completing the courses, which you can use to show employers you are knowledgeable in data science and improve your employment prospects.
6. HarvardX’s Professional Certificate in Data Science on edX
You will learn the essentials of data science using R through this professional certificate program. To do this, you must first learn how to program in R before moving on to statistics, probability, data modeling, inference, etc.
Additionally, this certificate will introduce you to tidyverse and other specialized data science tools like ggplot2, dplyr, etc.
Additionally, you will master the fundamental machine learning algorithms used in data science as well as Unix/Linux, git, GitHub, and RStudio.
A total of 9 courses are included in this certificate program: R foundations, visualization, probability, inference and modeling, productivity tools, wrangling, linear regression, machine learning, and the final capstone project.
You will receive an instructor-signed certificate from edX and HarvardX at the conclusion of the Professional Certificate in Data Science to prove your proficiency in Data Science with R.
7. MITx’s MicroMasters in Statistics and Data Science (edX)
You will learn the fundamentals of statistics, data science, and machine learning through the Statistics and Data Science MicroMasters program.
You will learn the proper methods for statistical inference and probabilistic modeling so that you can draw actionable conclusions from the data.
Additionally, you will comprehend the numerous machine learning algorithms, such as deep neural networks, clustering techniques, and both supervised and unsupervised methods.
Additionally, this MicroMasters program includes five courses: probability, data analysis in social science, fundamentals of statistics, machine learning using Python, and an exam that serves as a capstone in statistics and data science.
You will receive an edX and MITx certificate with an instructor signature at the conclusion of this course, along with the information necessary to pursue a future profession as a data scientist, data analyst, data engineer, business intelligence analyst, systems analyst, etc.