Programming and Machine Learning: 9 Free Data Science Courses from Harvard

In today's job market, data science has become one of the most sought-after talents. The ability to extract valuable insights from massive amounts of data has become critical in industries ranging from finance to healthcare and beyond. Harvard University, one of the most prestigious educational institutions in the world, has recognized the importance of data science and offers a collection of free courses to help you master the field. Edition AnalyticsInsight reviewed nine free courses from Harvard University that will help you gain the skills and knowledge you need to succeed in data science.

Photo: IStock

Programming

The first step in learning data science should be learning to code. To do this, you can use your preferred programming language - Python or R.

If you want to learn R, Harvard University offers a program Data Science: R Basics is an introductory R course designed exclusively for data science students.

This course will introduce you to R language topics such as variables, vector arithmetic, data types, and indexing. You'll learn how to work with data using tools like dplyr, as well as how to create graphs to visualize data.

If you prefer Python, you can take a free course CS50 Introduction to Programming with Python. This course will cover functions, variables, arguments, data types, conditional statements, loops, methods, objects, and other concepts.

On the subject: Fashion, design, languages, cooking: 10 free online courses to learn a new hobby

Both of the above programs are designed for self-study. The Python course is more detailed than the R program and takes longer to complete. Additionally, many courses are taught in R, so learning R can be helpful if you want to get up to speed with the program.

Data visualization

Visualization is one of the most effective strategies for communicating the results of data analysis to other people.

As part of the Harvard University program Data visualization You'll learn how to create visualizations in R using the ggplot2 package, and learn the concepts of data-driven communication.

Probability theory

As part of of this course You will learn important principles of probability theory needed to perform statistical testing on data. Topics covered include random variables, Monte Carlo simulation, independence, expected values, standard errors, and the central limit theorem.

The topics covered will be explored through case studies, allowing the knowledge gained to be applied to a real-world data set.

Statistics

You can get through this course after studying probability theory to master the principles of statistical inference and modeling.

This program will teach you how to determine estimates and margins of error, and introduce you to Bayesian statistics and the fundamentals of predictive modeling.

Productivity tools

This course in Project Management is an elective as it has no bearing on the study of data science. Instead, you'll learn how to use Unix/Linux for file management, GitHub, and R for reporting.

Knowing how to do these steps will save you a lot of time and help you manage complex data science projects more effectively.

Data preprocessing

The next course on this list is called Date Wrangling — it will teach you how to prepare data and put it into a format that is easily understood by machine learning models.

It covers importing data into R, working with string data, cleaning data, parsing HTML, and working with texts.

As a data scientist, you often need to extract data from publicly available sources on the Internet, such as a PDF document, an HTML web page, or a tweet. It's not always possible to get beautiful, structured data in a CSV file or Excel sheet.

By the end of this course, you will understand how to process and cleanse data to extract key insights from it.

Linear Regression

Linear regression is a machine learning technique that allows you to model a linear relationship between two or more variables. It can also be used to identify and correct contributing factors.

You may be interested in: top New York news, stories of our immigrants and helpful tips about life in the Big Apple - read it all on ForumDaily New York

As part of this course You'll learn about the theory behind linear regression models, how to explore the relationship between two variables, and how to find and eliminate confounding variables before developing a machine learning algorithm.

Machine learning

And finally course, which you've most likely been looking forward to. We will teach you about the basics of machine learning, as well as strategies, approaches to supervised and unsupervised modeling, and recommender systems.

Project Capstone

After completing all previous courses you will be able to complete the project in Data Science, which will test your abilities in data visualization, probability, statistics, data science, data organization, regression and machine learning.

In this capstone project, you will be able to use what you have learned in previous courses and complete a hands-on data science project from scratch.

Read also on ForumDaily:

Here's how to get military service exemptions to live and work in the U.S.

How to get grants and scholarships to study at an American college: complete instructions

Clock change: When will the US switch to daylight saving time?

Preparing your home for winter: 24 tips to help you survive the cold in comfort

Five Hollywood films that failed at the American box office, but became hits in the USSR

18 ghost cities in America that give goosebumps

How to become a millionaire: 11 tips from experts

In 20 years, these 14 things will be impossible to buy

Nine Promising Stocks You Can Buy for Under $5

Do you want more important and interesting news about life in the USA and immigration to America? — support us donate! Also subscribe to our page Facebook. Select the “Priority in display” option and read us first. Also, don't forget to subscribe to our РєР ° РЅР ° Р »РІ Telegram  and Instagram- there is a lot of interesting things there. And join thousands of readers ForumDaily New York — there you will find a lot of interesting and positive information about life in the metropolis.