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January 8, 2024
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Ever wondered why everyone's talking about Data Science, Machine Learning, and Artificial Intelligence? Well, because these skills can open up exciting opportunities and lead to well-paying careers. These skills are in high demand because they play a crucial role in making machines and systems smarter. As technology advances, there's a chance that some jobs currently done by people might be taken over by robots and bots equipped with these skills.
For programmers, it's a smart move to embrace these technologies and stay ahead in the job market. Companies are willing to pay higher salaries for professionals who understand data science, as it's changing the way we live and work. The good news is, Harvard University offers free courses on data science and AI through edX, making it easier for anyone to upgrade their skills and explore these exciting fields.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
Learn how to use Python to tackle real-world data science problems! This hands-on course will teach you to code in Python for tasks like modeling, statistics, and telling stories with data. We'll dive into popular libraries like Pandas, numPy, matplotlib, and SKLearn. You'll get to run simple machine learning models, see how well they work, and apply them to solve actual problems. By the end, you'll have a solid foundation in using Python for machine learning and artificial intelligence, setting you up for more advanced Python studies.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
Learn to visualize data using ggplot2 in R, progressing from basic datasets to real-world examples. Understand the importance of cautious data handling due to errors and biases, with a focus on effective communication through custom plots. Master data visualization principles, discover the strengths and weaknesses of popular plots, and acquire skills to uncover valuable insights for career advancement. This course provides a practical foundation for leveraging data through compelling visualizations.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
In this course, you'll learn the fundamentals of machine learning, including how to avoid training too much by using cross-validation. We'll cover different popular machine learning tricks and even show you how to make a recommendation system. We'll also explain what regularization is and why it's handy in machine learning. Join us to grasp these essential concepts and skills in a straightforward way!
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
In this course, you'll start with the basics of R language, learning simple R rules. It'll cover important R ideas like the types of data, doing math with sets of numbers, and picking out specific pieces of data. You'll also get the hang of doing things in R, like organizing data using dplyr and making charts. Join this course to build a solid foundation in R programming with easy-to-understand lessons.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
In this course, you'll learn how to bring data into R from various file types. This will cover web scraping, making data tidy with tidyverse for easier analysis, and working with strings using regular expressions (regex). You'll also get hands-on experience organizing data with dplyr, handling dates and times, and exploring text mining. Apply for this course to master these practical skills for working with data in a straightforward way.
Level: Beginner to intermediate
Duration: 8 Weeks
Certificate: Free to Audit, Paid
In this course, you'll grasp the ideas needed to figure out predictions and errors in data. Learn how to combine information from various sources using models. We'll also cover the fundamental concepts of Bayesian statistics and predictive modeling. Join this course to understand these essential concepts and improve your skills in making predictions with data.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
In this course, you'll discover how to handle your files using Unix/Linux. Learn the ropes of version control with git and set up a place for your projects on GitHub. Plus, find out how to make the most of handy tools in RStudio. Join this to pick up these practical skills for managing files and projects.
Level: Beginner
Duration: 8 weeks
Certificate: Free to Audit, Paid
In this course, you'll explore how Galton first came up with linear regression. Learn about confounding and how to spot it. Discover how to use linear regression in R to study the connections between different things. Join this course to understand these concepts and apply them in a straightforward way.
Level: Beginner
Duration: 2 Weeks
Certificate: Free to Audit, Paid
To become really good at being a data scientist, you need to practice a lot. This capstone project gives you a chance to use all the R data analysis skills you've learned from the above courses. The project tests your abilities in things like data visualization, figuring out probabilities, making predictions, and working with different types of data. Once you finish, you'll have something to show to future employers or schools, proving you're an expert in data science. It's a great way to demonstrate what you've learned!
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