Madza πŸ‘¨β€πŸ’»βš‘
Madza πŸ‘¨β€πŸ’»βš‘

@madzadev

10 Tweets 7 reads Oct 09, 2023
IBM is offering 12 Online Coding Courses πŸ”₯πŸ”₯
🐍 Python
πŸ§‘β€πŸ’» Data Science
✨ SQL
πŸ’½ NoSQL and DBaaS
πŸ“ˆ Statistics
🧠 R Programming
πŸ§™ Data Analytics
πŸš€ Artificial Intelligence
Open this to not miss your chance πŸ§΅πŸ‘‡
1. Python Basics for Data Science
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!
edx.org
2. Data Science 101
Find out the truth about what Data Science is. Hear from real practitioners telling real stories about what it means to work in data science.
cognitiveclass.ai
3. SQL for Data Science
Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field.
edx.org
4. NoSQL and DBaaS 101
In this NoSQL course, you will get an overview of the NoSQL database landscape, learn to create and replicate databases, load and query data, and conclude by pointing you to additional resources to continue your education.
cognitiveclass.ai
5. Statistics 101
Split into five modules, this is a beginner's course covering the fundamentals of statistics.
Learn about probability, what it means to group data by categorical variables, and how you can transform your data into graphs and charts.
cognitiveclass.ai
6. R Programming Basics for Data Science
This course introduces you to R language fundamentals and covers common data structures, programming techniques, and how to manipulate data all with the help of the R programming language.
edx.org
7. Data Analytics Basics for Everyone
Learn the fundamentals of Data Analytics and the data ecosystem, the process and lifecycle of data analytics, career opportunities, and the different learning paths you can take to be a Data Analyst.
edx.org
8. AI for Everyone: Master the Basics
Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning, and neural networks.
edx.org
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