Courses Files Repository

Published by SuperDataScience Team

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Welcome to the courses files repository page, here you will find a list of all the SuperDataScience courses with a link to they’re supplemental materials page.
- Data Science A-Z™: Real-Life Data Science Exercises Included
- Business Process Modeling A-Z™: Learn BPMN 2.0 From Scratch
- R Programming A-Z™: R For Data Science With Real Exercises!
- Data Driven Marketing A-Z: Improve Your Campaign Performance
- R Programming: Advanced Analytics In R For Data Science
- Python A-Z™: Python For Data Science With Real Exercises!
- Tableau 10 A-Z: Hands-On Tableau Training For Data Science!
- Machine Learning A-Z™: Hands-On Python & R In Data Science
- Power BI A-Z: Hands-On Power BI Training For Data Science!
- SQL & Database Design A-Z™: Learn MS SQL Server + PostgreSQL
- Deep Learning A-Z™: Hands-On Artificial Neural Networks
- Artificial Intelligence A-Z™: Learn How To Build An AI
- BPMN for Business Analytics A-Z
- Tableau Expert: Top Visualization Techniques in Tableau 10
- Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs
- Deep Learning and NLP A-Z™: How to create a ChatBot
- Blockchain A-Z™: Learn How To Build Your First Blockchain
- Intro to Data Science: Your Step-by-Step Guide To Starting
- Artificial Intelligence 2018: Build the Most Powerful AI
- Tableau 2018: Hands-On Tableau Training For Data Science!
- Tableau 2018 Advanced: Master Tableau in Data Science
- Introduction to Blockchain with Industry Applications
- Machine Learning Practical: 6 Real-World Applications
- AI for Business
- AI Masterclass
- Introduction to MongoDB
- Tableau for Business and Marketing
- Deep Reinforcement Learning 2.0
- Machine Learning Practical Workout | 8 Real-World Projects
- Machine Learning Regression Masterclass in Python
- Python for Statistical Analysis
- AI Bootcamp in R
- AI for Simple Games
- TF 2.0 Practical
- TF 2.0 Practical Advanced
- QlikSense Masterclass
- Modern NLP
- Tableau Certified Associate
- Data Manipulation in Python: A Pandas Crash Course
- MS Excel Exam Guide: Analyzing and Visualizing Data