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We’re 3 months into the new year. Wow, time is going by fast. With that being said, how many of you can say that you are on target to reach your goals, if it’s Q1 goals, learning goals, etc?
It’s hard. It’s hard to stay on top of everything and achieve every goal.
If learning data science was one of your 2024 goals, KDNuggets is here to help you so your journey to learning new skills and shifting careers is smooth.
I have put together a list of FREE online data science courses that will help you build a solid foundation of data science knowledge, skills and best practices to have a great career in the data world.
From: DataCamp
Link: Understanding Data Science
If you’re new to the data science world, the first thing you want to get your head around is the basics. With no coding involved, this free course will define what data science is.
You will dive deeper into what a data science workflow is and how data science is applied to real-world problems. Once you have a good understanding of the field, you will end off will learning about different roles within the data science field.
From: Harvard University
Link: Introduction to Programming with Python
Have you decided to choose Python as your programming language choice? Great idea.
It’s been a popular programming language for a while now and now you can learn it with this self-paced course which will take you roughly 10 weeks to complete. This course has been specifically designed for students who have no prior experience or knowledge when it comes to programming and wish to transition into the data science world by learning Python.
The following topics are covered: functions, variables, conditionals, loops, exceptions, libraries, unit tests, file I/O, regular expressions, object-oriented programming, and more.
From: DataCamp
Link: Python Data Science Toolbox
As it’s been the most popular programming language for a few years now, there is no harm in perfecting the Python programming language.
With no coding experience or skill needed, Part 1 of the Python Data Science toolbox course teaches you how to effectively analyze and visualise your data. With 13 videos included in this course, you will go from data manipulation to plotting data with Matplotlib.
From: Harvard University
Link: Data Science: R Basics
Maybe you haven’t gone for Python and maybe you have decided to choose R as your programming language. Regardless of what you decide to go ahead with – it is always good to start with the basics. Harvard University offers a Data Science: R Basics course that helps you to build a solid foundation in the R programming language – from learning how to wrangle, analyze, and visualize data.
The course is free; however, you can pay for a verified certificate for $149.
From: Stanford Online
Link: Statistical Learning
I say it all the time and I will say it again – it is very important to learn about statistics in data science. This Statistical Learning course by edX will provide you with the main tools used in statistical modelling and data science.
It covers the following topics: an overview of statistical learning, linear regression, classification, resampling methods, linear model selection and regularization, moving beyond linearity, tree-based methods, support vector machines, deep learning, survival modelling, unsupervised learning, and multiple testing.
From: Google
Link: Google Data Analytics
You have probably heard about this course a lot – it is very popular. It consists of 8 sections, where you will learn about the day-to-day use of data, best practices and processes that you should expect in your new data science/analytics jobs.
You will learn how to clean and organize data for the analysis process and make calculations using spreadsheets, SQL and R programming. It doesn’t stop there, you will further your analytical skills by creating data visualizations and also learning about tools such as Tableau.
From: Coursera
Link: Machine Learning Specialization
This course has been put together by Andrew Ng, Founder & CEO of Landing AI, Founder of deeplearning.ai, and Co-Chairman and Co-Founder of Coursera. He has constructed a machine learning specialization made up of 3 courses:
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning
These courses are free; however, there is a fee if you wish to get certified.
These 7 courses help you build skills in different aspects of data science, to ensure you have the skills and knowledge you require to be great at your data science job.
For example, working on being proficient in the Python programming language, or the R programming language. Understand the importance of learning statistics in data science, and how it affects the analytics process. Last but not least, put everything together and apply it to machine learning, for example, regression and recommenders.
Happy Learning!
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.
