This course gives you a complete overview of what it entails to be a Data Scientist. In this course you will learn about cleaning and preparing your data for analysis, performing basic visualization of your data, modelling your data, curve-fit your data and ultimately about presenting your findings to the audience. This course will prepare you for the real-world Data Science scenarios by giving you sufficient practical exercises and assignments. In addition, tools like SQL, SSIS, Tableau and Gretl are also covered.
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Course Syllabus
- Introduction
- Visualization
- Introduction to Tableau
- Tableau for Data Mining
- Advanced Data Mining
- Modelling
- Stats Refresher
- Simple Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Building a robust geo-demographic segmentation model
- Assessing your model
- Drawing insights from your model
- Model maintenance
- Data Preparation
- BI tools
- Data Wrangling before the load
- Uploading data using SSIS
- Handling errors during ETL
- SQL programming
- Data Wrangling after the load
- Handling errors during ETL
- Communication
- Working with people
- Presenting for Data Scientists
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