Study Plan

Math

1. Calculus
2. Linear Algebra

Data Structures and Algorithms

1. Basic Python
2. How to Solve Problems
3. Big O Notation
4. Collection data structures (lists, arrays, linked lists, queues, stack)
5. Recursion
6. Trees
7. Maps and Hashing
8. Binary Search
9. Sorting Algorithms
10. Divide & Conquer Algorithms
11. Greedy Algorithms
12. Graph Algorithms
13. Dynamic Programming
14. Linear Programming

Python and SQL

1. Basic SQL, SQL Joins, SQL Aggregations, subqueries
2. Python data types, operators, control flow, functions, scripting
3. Python Numpy
4. Python Pandas

Business Analytics

1. Statistics: descriptive, inferential, probability
2. Excel to manipulate, analyze and visualize data
3. Data visualization with Tableau

Predictive Analytics

1. Problem Solving with Advanced Analytics
2. Data Wrangling
3. Classification Models
4. A/B Testing
5. Time Series Forecasting
6. Segmentation and Clustering

Data Analysis

1. Introduction to Data Analysis: Anaconda, Jupyter, data analysis, Pandas and numpy
2. Practical Statistics: Probability, binomial distribution, conditional probability, stardardizing, sampling distribution, hypothesis testing, T-tests and A/B testes, regression, multiple linear regression, logistic regression
3. Data Wrangling: gathering, assessing, cleaning
4. Data Visualization with Python

Data Visualization

1. Dashboard Design
2. Data Storytelling