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The 2024 goals continue and I hope that all the people who wrote down learning data science as one of their goals come across this article. You can learn data science in many different ways, from YouTube videos to going back to University. 

However, if you do not have the finances to go back to university or you need more structure than YouTube can provide - I understand. 

if you are someone who likes to experience their learning journey on one platform, and it follows a curriculum and is organized - continue reading this blog. 

Here are 4 different learning roadmaps, for 4 different levels:

Introduction to Data Science

Level: Beginner

Link: Intro to Data Science Specialization 

If you are looking to start a career in data science or want to transition from your current career into data science - the first thing you need to do is look into the foundations of data science to understand what it’s all about. 

With this, you will develop the mindset to work like a data scientist and understand the different methodologies you can use to tackle different types of data science problems, with a 4-course series:

• What is Data Science?
• Tools for Data Science
• Data Science Methodology
• Databases and SQL for Data Science with Python

You will be able to complete this course in 1 month if you commit 10 hours a week. 

Data Science Fundamentals with Python and SQL 

Link: Data Science Fundamentals with Python and SQL Specialization

Level: Beginner/Intermediate 

When you feel like you have a very good understanding of what data science is, what it entails and where it can take you. Your next step is to dive a bit deeper into the fundamentals of data science with Python and SQL. 

In this 5 course specialized series, you will learn and develop hands-on experience with Jupyter, Python, and SQL as well as perform Statistical Analysis on real data sets:

• Tools for Data Science
• Python for Data Science, AI & Development
• Python Project for Data Science
• Statistics for Data Science with Python
• Databases and SQL for Data Science with Python

IBM Data Science Professional Certificate

Link: IBM Data Science Professional Certificate

Level: Intermediate/Expert

You are now ready to start your data science professional certificate journey. 

A 10-course series, where you will prepare for a career as a data scientist, by developing in-demand skills and hands-on experience, such as applying your new skills to real-world projects to get you job-ready.

The courses include: 

• What is Data Science?
• Tools for Data Science
• Data Science Methodology
• Python for Data Science, AI & Development
• Python Project for Data Science
• Databases and SQL for Data Science with Python
• Data Analysis with Python
• Data Visualization with Python
• Machine Learning with Python
• Applied Data Science Capstone

You will be able to complete this course in 5 months if you commit 10 hours a week. 

Advanced Data Science

Link: Advanced Data Science with IBM Specialization

Level: Expert

You have gone through the beginner courses, you have refined your Python and SQL skills, you dived deeper into data science with Python projects, data analysis, machine learning and more. But you want a bit more. 

This advanced data science specialization course will make you an expert in data science, machine learning and artificial intelligence. Consisting of four courses:

• Fundamentals of Scalable Data Science
• Advanced Machine Learning and Signal Processing
• Applied AI with DeepLearning
• Advanced Data Science Capstone

Become an IBM-approved Expert!

Wrapping it up

And that’s it - 4 different data science learning routes for 4 different levels. If you are starting from the beginning, then I would recommend taking all of them so that you can have everything under your belt. 

You have a simple data science learning roadmap all in one place - on one platform!
 
 

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.