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Day 1

09:00 - 09:40	09:45 - 11:00		11:10 - 12:20		12:25 - 13:00	13:00 - 14:00	14:00 - 15:00	15:00 - 18:00
Program Intro	Class Intro	10 mins Break	Lecture	5 mins Break	Lecture	Lunch Break	Lecture	Lab Work

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👉   Table of Contents

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📅   Week 1 Week 1 | Day1 `s Key Objectives: Housekeeping Issues and Bootcamp Expectation Trello Command Line Git & GitHub Jupyter Notebooks and Markdown
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Presentation] Intro [Activity] Command Line [Presentation] Git [Presentation] Jupyter Notebooks [Cheat Sheet] Mac Command [Cheat Sheet] Windows Command Line [Cheat Sheet] Git Cheat Sheet [Cheat sheet] Markdown Cheat Sheet [LAB] Git [LAB] Jupyter Notebook [LAB] (Optional) Bash	[Presentation] Conda [Activity] Conda Environment [Cheat Sheet] Conda Cheat Sheet [Presentation] Python Built-In Data Structures [Notebook] Python Built-In Data Structures [Presentation] Python String Operations [Notebook] Python String Operations [Lab] Python Built-In Data Structures [Lab] Python Strings	[Presentation] Python Functions [Notebook] Python Functions [Presentation] Python Lists Comprehension [Notebook] Python Lists Comprehension [Lab] Pre-Work Review	[Presentation] Programming Tips [Presentation] Programming Code Simplicity [Presentation] Lambda Function [Presentation] Data Analysis Intro [Presentation] Data Analysis Process [Presentation] Numpy Arrays [Cheat Sheet] Numpy Arrays [Notebook] Numpy Arrays [Lab] Data Gathering [Lab] Numpy Arrays	[Presentation] Python Map [Presentation] Intro to Pandas [Code Along] Intro to Pandas Weekly Recap Weekly Retro [Lab] Pandas Exercises

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📅  Week 2 - Exploratory Data Analysis

📅   Week 2 Week 2 | Day5 `s Key Objectives: Weekly Recap Pandas Group By Pandas Merging Pandas Best Practices Week 2 | Day4 `s Key Objectives: Data Pipelining Linear Regression Week 2 | Day3 `s Key Objectives: Correlation and correlation Matrix Plotting using Matplotlib and seaborn Exploratory Data Analysis Week 2 | Day2 `s Key Objectives: HealthCare For All Case Study Data Cleaning using Pandas Statistics basics ( samples, probability, distributions, random variables, samples, measures of central tendency and dispersion) Week 2 | Day1 `s Key Objectives: Pandas contd(filtering, missing values, applying functions, concatenating, IO operations) HealthCare For All Case Study Data Cleaning using Pandas
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Code Along] Pandas_Part_2 [Healthcare For All Case Study] [Code_Along] Healthcare For All Case Study [Lab] EDA_Round_1	[Presentation] Basic Statistical Concepts [Lab] EDA_Round_2	[Presentation] Correlation of Numerical Features [Presentation] EDA with plotting [Notebook] EDA with plotting [Cheat Sheet] Matplotlib [Cheat Sheet] Seaborn [Lab] EDA_Round_3	[Linear Regression Overview] [Code_Along] Data_Pipelining [Case Study Presentations] [Lab] EDA_Round_4	[Presentation] Pandas Joining, Grouping [Notebook] Pandas contd Weekly Recap Weekly Retro Kahoot [Lab Pandas Group By]

📅   Week 3 - Databases, Tableau

Week 3 Week 3 | Day 5 `s Learning Objectives: Storytelling with Data Data Visualization Tableau MongoDB Weekly Recap Week 3 | Day 4 `s Learning Objectives: Data Warehousing Data Visualization Tableau Week 3 | Day 3 `s Learning Objectives: Subqueries Temporary Table Views Connect Python to MySql Week 3 | Day 2 `s Learning Objectives: ERDs Joins Week 3 | Day 1 `s Learning Objectives: Relational Databases SQL Queries
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Presentation] Relational Databases [LAB] Lab | SQL Intro [LAB] Lab | SQL Queries	[Presentation] Joins & ERD [Activity ERD] [Lab] Sql Join two tables [Lab] (optional) Sql Join multiple tables	[Presentation] SQL Sub Queries [Presentation] Temporary Table/ Views [Presentation] Connect Python into MySQL [Notebook] Connect Python into MySQL [Lab] SQL Sub Queries	[Presentation] Data Warehousing [Presentation] Intro to Tableau [Presentation] Data Visualisation [LAB] Tableau [Lab] (Optional) SQL Group By	[Presentation] Tableau [Presentation] Storytelling with Data] Weekly Recap [Demo] No-SQL Databases MongoDB Weekly Retro [LAB] Tableau Dashboard [Lab] [Optional] Resume using Tableau

📅   Week 4 - Regression

Week 4 Week 4 | Day 5 `s Learning Objectives: Hypothesis Testing - Two Sample Test Recap Week 4 | Day 4 `s Learning Objectives: Hypothesis Testing Model Validation Week 4 | Day 3 `s Learning Objectives: Data Engineering Linear Regression. Model Validation. Week 4 | Day 2 `s Learning Objectives: Linear Regression. Model Validation. Week 4 | Day 1 `s Learning Objectives: Machine Learning Intro. Distributions. Data Transformation.
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Presentation] Intro to Machine Learning Guest Speaker, CTO [Presentation] Probability Distributions [Presentation] Data Processing [LAB] Lab | Data Transformation	[Presentation] Linear Regression [Notebook] Linear Regression [LAB] Lab | Model Fitting and Evaluating	[Guest Speaker] Data Engineering, Xing [Presentation] Improving Model Accuracy [Notebook] Linear Regression [LAB] Model Evaluation and Improving	[Presentation] Sampling Distributions [Presentation] Hypothesis Testing [Notebook] Hypothesis One Sample Test [LAB] Model Evaluation and Improving [Lab] Hypothesis Testing	Kahoot [Presentation] Two Sample T-Test [Notebook] Hypothesis Two Sample Test Weekly Recap Weekly Retro Midterm Project Intro/ Briefing [Lab] Hypothesis Testing

📅   Week 5 - Mid Term Project

Week 5 Mid-Term Project
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
Submitting project plans	Work on the project	Work on the project	Work on the project	Work on the project
Work on the project				Presentations

📅   Week 6 - Song Recommender Project

Week 6 Week 6 | Day 4 `s Learning Objectives: Unsupervised Learning K-means Algorithm Saving/Loading Model using Pickle Week 6 | Day 3 `s Learning Objectives: APIs. Spotify API. JSON format overview. Restful APIs Week 6 | Day 2 `s Learning Objectives: Web Scraping multiple pages Python modules Week 6 | Day 1 `s Learning Objectives: Git ignore Web Scraping HTML, CSS Beautiful Soap
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Case Study] Gnod Song Recommender [Presentation] Web Scraping [Activity] CSS Selector [Notebook] Web Scraping Code Along [Presentation] Project Roadmap [LAB] Song Recommender Project	[Notebook] Web Scraping Multiple Pages Code Along [Code Along] Python Modules with VS Code [LAB] Song Recommender Project	[Presentation] APIs [Presentation] Spotipy [Notebook] APIs [Notebook] Spotipy [LAB] Song Recommender Project	[Presentation] Clustering using K-means [Presentation] K-Means with Scikit-Learn [Notebook] K-Means Code Along [LAB] Song Recommender Project	[Presentation] Weekly Recap [Weekly Retro] [LAB] Song Recommender Project

📅   Week 7 - Advanced ML Topics

Week 7 Week 7 | Day 5 `s Learning Objectives: Random Forest Hyper Parameter Tuning ML Frequent Problems Recap Week 7 | Day 4 `s Learning Objectives: Cross Validation Handling Imbalanced Data Bias and Variance Tradeoff Week 7 | Day 3 `s Learning Objectives: Decision Trees Week 7 | Day 2 `s Learning Objectives: PCA Logistic regression Evaluating Classification models Week 7 | Day 1 `s Learning Objectives: Feature Selection KNN
Day 1	Day 2	Day 3	Day 4	Day 5 It is Friday!! 🥳😎✌️
[Presentation] Feature Selection [Presentation] KNN [Notebook] Feature Selection [Notebook] Feature Selection using P-Value [Notebook] KNN [LAB] Model_Comparision	[Presentation] PCA [Presentation] Logistic Regression [Presentation] Evaluating Classification Models [Notebook] PCA [Notebook] Logistic Regression [LAB] (Optional) PCA [LAB] Logistic Regression	[Presentation] Decision Trees [Notebook] Decision Trees [Lab] Decision_Trees	[Presentation ] Cross Validation [Presentation] Bias & Variance [Notebook] Cross Validation [Notebook] Handling Imbalanced Data sets [Lab] Cross Validation & Resampling	Kahoot [Presentation] ML Frequent Problems [Presentation] Ensemble Methods [Presentation] Weekly Recap [Notebook] Random Forest [Notebook] Hyper Parameter Tuning [Weekly Retro] [Lab] Random Forest & Hyper Parameter Tuning

📅   Week 8 - Advanced-ML & Final Project

Week 8 Week 8 | Day 2 `s Learning Objectives: NLP Text Analytics Week 8 | Day 1 `s Learning Objectives: Agile, MVP. Final Project Kickoff. Final Project Presentation Example. Object Oriented Programming*.
Day 1	Day 2	Day 3	Day 4	Day 5
[Presentation] Agile/ Project Management Final Project Kick off Object Oriented Programming*	[Guest Speaker] [Presentation] Natural Language Processing [Notebook] NLP [Data] NLP Data	Final Project Elevator Pitches	Daily Standup Final Project Plan Submission	Daily Standup

📅  Week 9 - Final Project