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Somewhere, someone is speaking about wanting to break into the tech world. If it’s to become a software engineer or they’re interested in data science. When these people start their data science journey, in particular, there are a variety of online courses, boot camps, and degrees to choose from. It can be very difficult, so that’s where I come in and take the workload off of you. 

So, let’s go straight into it…

Introduction to Data Science with Python - Harvard

Courses Link: Introduction to Data Science with Python

Harvard University is a well-known private Ivy League research university. To meet the rising demand for technology professionals in today’s market, they understand the importance of providing interested or new students with free material to kick-start their journey in the tech world. 

The above course is aimed at newbies into the data analytical world. The most popular programming language for data science at the moment is Python, therefore that is always a good place to start. The course consists of you committing 3-4 hours per week, in which you will learn about:

• Study regression models
• Utilize popular libraries such as sklearn, Pandas, matplotlib, and numPy
• Machine learning concepts such as overfitting, assessing uncertainty, and weighing trade-offs
• Fundamental understanding of machine learning models
• Basic concept understanding of Machine Learning (ML) and Artificial Intelligence (AI)

If you are looking for other courses, Harvard also offers:

• Data Science: Probability
• Data Science: Linear Regression
• Data Science: Visualization
• Data Science: Productivity Tools
• Data Science: Machine Learning
• High-Dimensional Data Analysis

Statistical Thinking And Data Analysis - MIT

Link: Statistical Thinking And Data Analysis

MIT is also another leading learning institute. In the year of 2001, they launched a platform called OpenCourseWare. This is another learning institute that understands the demands of providing free educational material for people to understand a new market and their new potential careers. 

Statistical thinking and implementation in data analysis is a very important concept. Some say that statistics is useful but not mandatory for you to know the ins and outs, but in my time as a data scientist, I have understood the importance of statistics and how it could have improved and fast-tracked my career. 

In this course, you will have to commit to 2 sessions per week that run for 1.5 hours each, and you will learn about:

• Probability
• Discuss sampling techniques
• Data summarization
• Common sampling distributions
• Statistical inference and hypothesis testing
• Regression
• Nonparametric inference

Other data analytics courses provided by MIT:

• Communicating With Data
• Advanced Data Structures
• How to Process, Analyze and Visualize Data
• Mathematics Of Big Data And Machine Learning

Introduction to Data Analytics - IBM

Link: Introduction to Data Analytics

International Business Machines Corporation is not a university, but its courses are well-recognized and provide newbies with the right learning materials to kickstart a new journey. With 397,828 already enrolled in the course and taught in 8 languages, this introduction to data analytics course provides people with a smooth entry into the data world. 

This course is flexible and requires you to commit approximately 10 hours to learn about:

• What Data Analytics is and the key steps
• Different types of data structures, file formats, and sources of data
• Describe the data analysis process involving collecting, wrangling, mining, and visualizing data
• Differentiate between different data roles

Mining Massive Data Sets - Stanford University 

Course Link: Mining Massive Data Sets

Another leading university with great learning material is Stanford University. If you’re seriously thinking about taking up data analytics, it is also good to understand the more popular and fast-developing areas of the tech world, such as machine learning and artificial intelligence. Naturally, a lot of data analysts move on to working on machine learning models and then find their niche, such as natural language processing. 

A part of the machine learning world is dealing with mining massive datasets. This course is a 7-week course, and you will learn about the following:

• MapReduce
• Algorithms for extracting models 
• Information from large datasets

If you are interested in machine learning, artificial intelligence, and deep learning, the following courses may be of interest to you:

• CS 221 — Artificial Intelligence
• CS 229 — Machine Learning
• CS 230 — Deep Learning

Introduction to Artificial Intelligence - Berkeley

Link: Introduction to Artificial Intelligence

If you’ve already down-packed your knowledge on data analytics and you’re ready to kickstart a career or your learning journey in artificial intelligence, then Berkeley University has a great introduction to artificial intelligence course. 

The course is 8 weeks long, and in the link provided, you will have the lecture topics provided in different formats, reading notes, and homework. The course starts with the basic ideas and techniques around the design of intelligent computer systems, which goes into a further deep dive into statistical and decision-theoretic modeling paradigms.

Wrapping it up

These 5 free data analytics courses will take you through a journey of the data world. You will start off with learning the basics and gradually move into more technical aspects of what it really consists of being a data analyst/scientist.
 
 

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.