Free Data Science Courses Online

11-Apr-2022

Companies and organizations across the globe are migrating toward big data, machine learning, and AI, Consequently, there is an upward surge in the trending demand for data science roles. This demand is taking a sustained and accelerating trend that is going to increase in the coming future. With the field of data science poised to offer rewarding career choices, data science is becoming a highly in-demand field. This, however, comes with the challenge of insufficient supply or lack of qualified professionals. Hence, data science courses and training have become even more critical. 

For those wishing to begin a career journey in data science and looking for a good training course, you may like to consider these few free data science courses online, to begin with. We have curated some of the most popular and the best free data science courses that anyone interested can avail of and access.

Johns Hopkins University- The Data scientist's Toolbox

This course will give you an overview of the most important tools and concepts in the data scientist's toolbox. This course provides an overview of the data, questions, and techniques used by data analysts and data scientists. This course is divided into two parts. The first part will give the conceptual overview of terminologies and concepts that are vital in the conversion of data into usable knowledge. The second section is a hands-on introduction to the program's tools, such as version control, markdown, GitHub, Git, R, and RStudio.

IBM- Tools for Data Science

This course will be an exposure to the most widely used data science tools, methods, ways of utilizing them, and the features they offer. A few of them are Jupyter Notebooks, RStudio IDE, JupyterLab, GitHub, Git, and Watson Studio, all of these are covered in this course. You'll learn what each tool is used for, what programming languages it can execute, as well as its benefits and drawbacks. You can test each tool and follow instructions to run simple code in Python, R, or Scala with the tools hosted in the cloud on Skills Network Labs. To complete the course, you will develop a final project using IBM Watson Studio and demonstrate your ability to prepare a notebook, write Markdown, and share your work with your peers using a Jupyter Notebook.

Google- Data Analysis with R programming

This course is the seventh certification course offered by Google. In this course, you will get to learn to use the R programming language. Participants will get to learn to work with R using RStudio which is a popular programming environment. This course will also go over R-specific software programs and tools, such as R packages. You'll learn how to clean, organize, analyze, display, and report data in new and more powerful ways using R. Current Google data analysts will continue to teach and demonstrate how to complete common data analyst duties using the most up-to-date tools and resources. The best part of this course is that participants of this certificate program will be prepared to apply for entry-level data analyst positions. There is no need for participants to have any prior experience.

Knight Center- Introduction to R for Journalists

The Knight Center for Journalism in America's massive open online course (MOOC). This course titled - titled "Introduction to R for Journalists: How to Find Great Stories in Data" is featured on their resource page. The course is a resource online and is actually a five-week course that was held in 2018. It is now available and accessible by any individual interested in learning how to utilize the statistical computing and graphics language R to improve data analysis and reporting for free. Andrew Ba Tran taught the course, which was funded by the Knight Foundation. He produced and curated the course's curriculum, which includes video lessons and tutorials, readings, and activities, among other things.

The University of Michigan - Introduction to Data Science in Python

This course will expose participants to the fundamentals of the Python programming environment, including lambdas, R, NumPy library, and reading and manipulating CSV files. The course is extensive with training involving techniques of data manipulation and cleansing by employing the popular library of Python. Additionally, it also teaches the abstraction of series and Dataframes as primary data structures essential for data analysis. Participants also get access to tutorials on effective utilization of functions such as merge, group, and pivot tables. Through this course, participants can expect to gain the ability to take tabular data, clean it, alter it, and execute basic inferential statistical analyses by the end of this course.

This course should be taken prior to any other Applied Data Science with Python courses, such as Applied Plotting, Charting, and Data Representation in Python, Applied Social Network Analysis, Applied Machine Learning, and Applied Text Mining in Python.

Kaggle - Become a Data Analyst

Competent and efficient Data Analysts have a distinct set of abilities that add significant value to companies looking to make data-driven business choices. You'll learn how to utilize Python, SQL, and statistics to uncover insights, explain key results, and create data-driven solutions in this class. The demand for qualified Data Analysts is increasing, and as a graduate of this program, you will be ready to fill these positions. To unearth insights, communicate crucial findings, and create data-driven solutions, use Python, SQL, and statistics.

MIT (Massachusetts Institute of Technology)- The Analytics Edge

This course will teach participants how to leverage data and analytics to give their careers and lives a boost. Through this course, they'll look at real-world instances of how analytics have helped a company or industry improve considerably. For instance IBM Watson, Twitter, Moneyball, Netflix, eHarmony, etc. This course will teach you the following analytics methods through these and other examples: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. To create models and interact with data, we will use the statistical software R. The lesson will be made up of lecture videos that are broken down into short chunks of 4 to 8 minutes each. Participants will be asked a "quick question" after each lecture segment to gauge their comprehension of the topic. A recitation will follow, in which one of the teaching assistants will go over the methods presented with a new example and data set. Each week, participants will be given a homework assignment that will require them to deal with various data sets in R or LibreOffice.

Datacamp- Introduction to SQL

A data scientist's job is to turn raw data into useful information. Much of the world's raw data, from electronic medical records to customer transaction histories, is stored in relational databases, which are organized collections of tables. To be a successful data scientist, you must be able to manipulate and extract data from databases using the SQL programming language. This course teaches SQL syntax that is common to various databases, including PostgreSQL, MySQL, SQL Server, and Oracle. This free data science course online will teach you all you need to know about databases so you can start working with them right away.

LinkedIn Learning- Become a Data Analyst

Data analysts use data analysis tools to analyze data and assist their teams in developing insights and business plans. You'll require arithmetic, statistics, communication, and experience working with data analytics and data visualization technologies. Investigate this in-demand profession. Through this course, participants will acquire the technical skills needed for a job as a data analyst. They will develop their skills in high-demand analysis software. Additionally get to develop abilities in communication, teamwork, and problem-solving.

University of California, San Diego - Introduction to Big Data

Individuals who are interested in learning more about the Big Data landscape will find this free data science course online exceptionally helpful. This course is for those who are new to data science and want to learn why the Big Data Era exists. It is intended for those who want to learn the vocabulary and fundamental principles underlying big data problems, applications, and systems. It's for individuals who want to start thinking about how Big Data might help them in their business or profession. It gives an overview of Hadoop, one of the most popular frameworks for big data analysis, which has made big data analysis easier and more accessible, allowing data to revolutionize our world.

IBM- Data Analyst

You'll master the fundamentals of data analysis, get hands-on practice, and get the expertise to assist firms in making better business decisions. You'll use Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics to deal with a variety of data sources, project situations, and data analysis tools. These online learning resources will provide you with hands-on experience manipulating data and applying analytical and data visualization approaches.

Participants do not require prior programming or knowledge of statistics and this course is ideal for those with no college diploma as well. To get started, all you need is a desire to learn, basic computer literacy, comfort dealing with numbers, high school math, and a desire to add essential skills to your resume.

Stanford University- Mining Massive Datasets

The course is based on the book Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, and Jeff Ullman, who also happen to be the course professors. The book is published by Cambridge University Press, however, you can get a free copy by contacting the publisher. The content of this online course closely resembles that of Stanford's CS246 course. The course includes major topics as given below:

• MapReduce systems and algorithms,
•  Locality-sensitive hashing, 
• Algorithms for data streams, 
• PageRank and Web-link analysis,
•  Frequent itemset analysis,
•  Clustering,
•  Computational advertising, 
• Recommendation systems, 
• Social-network graphs, 
• Dimensionality reduction
•  Machine-learning algorithms

University of Illinois- Data Visualization

Learn about the fundamentals of data mining, including approaches and applications through this free data science course online. Then delve into one of data mining's subfields: pattern discovery. Pattern discovery in data mining is covered in detail, including concepts, methods, and applications. We'll also go over pattern-based categorization algorithms and some fascinating pattern discovery applications. This course will teach you how to practice and engage in scalable pattern discovery methods on vast transactional data, discuss pattern evaluation measures, and investigate methods for mining a variety of patterns, sequential patterns, and sub-graph patterns, among other things.

Careerera- Data Science Fundamental (DSF)

This course is completely ideal for beginners as it introduces them to the core fundamentals of data science. The course agenda includes terminologies for Beginners,  What is Data Science and How Does It Work, Applications of Data Science, Using Statistics to Have Fun with Data, and Dealing with Data – An Example Python is a programming language. Participants in this course will learn about Data Science as a result of the training, and understand the fundamentals of data management and also Python for Statistical Report Visualization.

Those are some of the best free data science courses online that any interested and prospective professionals can access and avail themselves at the convenience of their own time and schedule. Although these free data science courses may not ideally fulfil your requirements if you are interested in pursuing a career in data science, beginning with these free data science courses online will help you have a grasp of the data science profession. Get started now and begin your exciting data journey.

Related Blog Posts

• What is Data Visualization?
• What is Data Mining
• What Qualifications are Required for the Position of a Data Analyst?
• What are the Pros and Cons of Data Science?
• Why Should You Study Data Science?

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