Objectives

Before entering a new field it is important to understanding the fundamentals. For this course we decided to focus heavily on statistics to help you start building the foundations, helping you better understand probability, bayesian thinking and inferential and descriptive statistics. We also thought it necessary to introduce you to SQL to better understand how to both build and query data from relational databases. When it comes to programming we place more emphasis on logic and helping students understand not just how to do something, but the why and the understanding of the logic behind each solution.

This program is designed for students who have limited to no experience with programming and statistics, while intense, it is achievable if you invest enough time and fully leverage your mentor's expertise. You will have weekly tutorial with a mentor to ask questions based on what you have completed in a given week and access to proprietary study material.

We have designed this course to be valuable to students who want to start the process of pursuing a career in data analysis, data science and data engineering, people who want to build a high level understanding of the data science process and develop some level of practical understanding of what data scientists/analysts/engineers do. Lastly, in order to help you communicate technical projects to a non technical audience, you will be required to explain your project to a panel or mentors and fellow students. Through this process you will be expected to communicate your work, along with the expected impact and recommendations derived from your findings.

Eligibility

The only criteria for pursuing this course is that you must have access to WiFi and a working laptop.

Course Outline

  • Introduction to Statistics for Data Science

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  • Introduction to Python and Pandas

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  • Introduction to SQL

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  • Using data to tell a story/ Data Visualization

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  • Introduction to Linear Algebra for Data Science

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  • Introduction to Machine Learning

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  • Building your first project

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  • Building your second project

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  • Case Study and Group Project

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