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Today

09:00 - 09:30	09:30 - 10:10		10:20 - 11:30		11:40 - 12:30	12:30 - 13:45	13:45 - 15:00	15:00 - 18:00
Warm up	Lab Review/Lecture	10 mins Break	Lecture	10 mins Break	Lab	Lunch Break	Lecture	Lab

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👉   Table of Contents

📅   Week 1 Week 1 | Day5 Key Objectives: Map function Intro to Pandas. Weekly Recap Week 1 | Day4 Key Objectives: Programming Tips and coding efficiency. Lambda functions. Data Analysis Intro and Process Numpy Arrays Week 1 | Day3 Key Objectives: Python functions Python List comprehension Pre-work review Week 1 | Day2 Key Objectives: Conda: Package and Environment Manager Python Data Structures: Lists, Tuples, dictionaries, Sets Python String Operations Week 1 | Day1 Key Objectives: Housekeeping Issues and Bootcamp Expectation Command Line Git & GitHub Jupyter Notebooks and Markdown
Monday	Tuesday	Wednesday	Thursday	Friday 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] Numpy Arrays	[Presentation] Python Map [Presentation] Intro to Pandas [Code Along] Intro to Pandas Weekly Recap Weekly Retro [Lab] Pandas Exercises

📅   Week 2 - EDA

📅   Week 2 Week 2 | Day1 Key Objectives: Pandas continued (filtering,applying functions, concatenating, IO operations) HealthCare For All Case Study Data Cleaning using Pandas Week 2 | Day2 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 | Day3 Key Objectives: Correlation and correlation Matrix Plotting using Matplotlib and seaborn Exploratory Data Analysis Week 2 | Day4 Key Objectives: Data Pipelining Linear Regression Week 2 | Day5 Key Objectives: Weekly Recap Pandas Group By Pandas Merging Pandas Best Practices
Monday	Tuesday	Wednesday	Thursday	Friday 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 [Lab] EDA_Round_4	[Presentation] Pandas Joining, Grouping [Notebook] Pandas contd Weekly Recap Weekly Retro Kahoot [Case Study Presentations] [Lab Pandas Group By]

📅   Week 3 - Databases - Visualizations

📅   Week 3 Week 3 | Day 5 Learning Objectives: Business Intelligence Tableau Weekly Recap Week 3 | Day 4 Learning Objectives: Having clause Temporary Table Data Warehousing Data Visualization Intro Tableau Week 3 | Day 3 Learning Objectives: Subqueries Week 3 | Day 2 Learning Objectives: ERDs Joins Week 3 | Day 1 Learning Objectives: Relational Databases SQL Queries
Monday	Tuesday	Wednesday	Thursday	Friday It is Friday!! 🥳😎✌️
[Presentation] Relational Databases [LAB] Lab | SQL Intro [LAB] Lab | SQL Queries	[Presentation] Joins & ERD [Lab] Sql Join two tables [Lab] (Optional) Sql Join multiple tables	[Activity ERD] [Presentation] SQL Sub Queries [Lab] SQL Sub Queries	[SQL Having clause] [Presentation] Data Warehousing [Presentation] Temporary Table/ Views [Presentation] Intro to Tableau [LAB] Tableau [Lab] (Optional) SQL Group By	[Presentation] Tableau [Presentation] Business Intelligence [Activity] KPIs Weekly Recap Weekly Retro [LAB] Tableau Dashboard

📅   Week 4 - Stats - Regression

📅   Week 4 Week 4 | Day 5 Learning Objectives: Hypothesis Testing Mid term project briefing Recap Week 4 | Day 4 Learning Objectives: Model Validation Revisit StandardScaler fit and transform functions Using the model to predict on a new unseen record. Hypothesis Testing Week 4 | Day 3 Learning Objectives: Linear Regression. Model Validation. Week 4 | Day 2 Learning Objectives: Linear Regression. Model Validation. Week 4 | Day 1 Learning Objectives: Storytelling with Data Data Visualization Machine Learning Intro. Data Transformation.
Monday	Tuesday	Wednesday	Thursday	Friday It is Friday!! 🥳😎✌️
[Presentation] Data Visualization [Presentation] Storytelling with Data] [Presentation] Intro to Machine Learning [Presentation] Probability Distributions [Presentation] Data Processing [LAB] Lab | Data Transformation [Lab] [Optional] Resume using Tableau	[Presentation] Linear Regression [Notebook] Linear Regression [LAB] Lab | Model Fitting and Evaluating	[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] A/B Testing [Notebook] A/B Testing Weekly Recap Weekly Retro Midterm Project Intro/ Briefing [Lab] Hypothesis Testing

📅   Week 5 - Mid Term Project

📅   Week 5 📅   Mid-Term Project
Monday	Tuesday	Wednesday	Thursday	Friday 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 Product

Week 6 Week 6 | Day 5 Learning Objectives: Working on the product Week 6 | Day 4 Learning Objectives: Unsupervised Learning K-means Algorithm Saving/Loading Model using Pickle Week 6 | Day 3 Learning Objectives: APIs. Spotify API. JSON format overview. Restful APIs Week 6 | Day 2 Learning Objectives: Web Scraping multiple pages Python modules Week 6 | Day 1 Learning Objectives: Git ignore Web Scraping HTML, CSS Beautiful Soup
Monday	Tuesday	Wednesday	Thursday	Friday 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 [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 [LAB] Song Recommender Project Song Recommender Presentations

📅   Week 7 - Machine Learning - Advanced

Week 7 Week 7 | Day 5 Learning Objectives: Random Forest Hyper Parameter Tuning ML Frequent Problems Recap Week 7 | Day 4 Learning Objectives: Cross Validation Handling Imbalanced Data Bias and Variance Tradeoff Week 7 | Day 3 Learning Objectives: Decision Trees Week 7 | Day 2 Learning Objectives: KNN Logistic regression Evaluating Classification models Week 7 | Day 1 Learning Objectives: Feature Selection
Monday	Tuesday	Wednesday	Thursday	Friday It is Friday!! 🥳😎✌️
[Presentation] Feature Selection [Notebook] Feature Selection [Notebook] Feature Selection using P-Value [Weekly Retro] [LAB] Model_Comparision	[Presentation] KNN [Presentation] Logistic Regression [Presentation] Evaluating Classification Models [Notebook] KNN [Notebook] Logistic Regression [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 [Data] Imbalanced Data Set [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 1 Learning Objectives: Agile Final Project Kickoff. Final Project Presentation Example. NLP
Monday	Tuesday	Wednesday	Thursday	Friday It is Friday!! 🥳😎✌️
[Presentation] Agile/ Project Management Final Project Kick off [Presentation] Natural Language Processing [Notebook] NLP [Data] NLP Data	Final Project Research	Final Project Elevator Pitches	Daily Standup Final Project Plan Submission	Daily Standup

📅  Week 9 - Final Project - Hackshow