README.md

Cohort FT-011121

Phase 1

Phase 1 Topic 01 - Getting Started with Data Science

• Data Science
  • DataScienceIntro.ipynb

Recordings

Title	Date	URL
Introduction to Data Science	2021-01-11	youtu.be/R7pM6SluD60

Phase 1 Topic 02 - Bash and Git

• Bash
  • command_line_basics.ipynb
• Git & GitHub
  • git_intro.ipynb
  • github.ipynb
  • Git Tools

Recordings

Title	Date	URL
Command Line Basics	2021-01-11	youtu.be/fjZFp2oTveg
Intro to Using Git with GitHub	2021-01-12	youtu.be/GGh9X5Iby10

Phase 1 Topic 03 - Control Flow, Functions, and Statistics

• Python
  • core_python.ipynb
• Coding Conventions
  • coding_best_practices.ipynb

Recordings

Title	Date	URL
Python Conventions & Best Practices	2021-01-11	youtu.be/3YxS_5dW3aY
Python Basics	2021-01-11	youtu.be/0ffOdnVmjHg
Some More Python Basics: Control Flow	2021-01-12	youtu.be/iLrqpbZvWb0
More Python: Functions	2021-01-13	youtu.be/FrklluKZWHw

Phase 1 Topic 04 - Python Libraries: Numpy and Pandas

• NumPy
  • intro_to_numpy.ipynb
  • numpy_intro_activity.ipynb
• Pandas
  • from_numpy_to_pandas.ipynb

Recordings

Title	Date	URL
Intro to NumPy	2021-01-13	youtu.be/-z-n8Hrtvl8
Intro to Pandas from NumPy	2021-01-15	youtu.be/S7p2w4cXc9o

Phase 1 Topic 05 - Data Cleaning in Pandas

• Data Cleaning
  • manipulating_data.ipynb
  • exploring_data.ipynb
  • data_cleaning_with_pandas_overview.ipynb
• Aggregation
  • aggregation.ipynb

Recordings

Title	Date	URL
More Pandas: Exploring and Manipulating Data	2021-01-19	youtu.be/m67HtpXYv3U

Phase 1 Topic 06 - Data Visualization

• Warmup
  • visualization_warmup.ipynb
• Data Visualization
  • motivation.ipynb
  • how_to_use_visualizations.ipynb
  • good_visualizations.ipynb
  • down_with_pie_chart.ipynb

Recordings

Title	Date	URL
Concepts of Data Visualization	2021-01-20	youtu.be/AxlWpplunVo

Phase 1 Topic 07 - SQL and Relational Databases & Phase 1 Topic 08 - Other Database Structures

• SQL
  • intro_to_sql.ipynb
  • using_sql.ipynb
  • sql_lesson.ipynb
  • sql_exercises.ipynb
  • joins.ipynb
  • advanced_topics.ipynb
• SQLite
  • sqlalchemy.ipynb
  • sqlite.ipynb
• NoSQL
  • nosql_intro.ipynb
  • mongodb.ipynb

Recordings

Title	Date	URL
SQL with Python & Pandas	2021-01-22	youtu.be/VFN89HOa9m0

---

Curriculum (v2.1)

Module 1

Module 1 Section 01 - Getting Started with Data Science

• Python
  • core_python.ipynb
• Coding Conventions
  • coding_best_practices.ipynb

Recordings

Title	Date	URL
The Data Science Process	2020-01-23	youtu.be/UZlPoaD4Bvw
Python Basics & Coding Practices	2020-01-23	youtu.be/uw4in0E8vvE

Module 1 Section 02 - Bash and Git

• Bash Shell (Command Line Interface)
  • command_line_basics.ipynb
• Git & GitHub
  • git_intro.ipynb
  • github.ipynb
  • git_collaboration.ipynb
  • git_advanced.ipynb
• Activities
  • git_collaboration_activity.ipynb
• Extras for Using Git
  • Git/Tools/

Recordings

Title	Date	URL
Forking a GitHub Repo	2020-01-22	youtu.be/SOKH8Xni_BE
Copy GitHub Repo Without Forking	2020-01-22	youtu.be/q0_MMK8AS8E
Command Line Basics	2020-01-28	youtu.be/Nta5HpFKDRc
The Git Basics	2020-01-28	youtu.be/Rx85RNB4gn4
GitHub Basics with Git	2020-01-28	youtu.be/F-VQbMxgm1o

Module 1 Section 03 - Control Flow, Functions, and Statistics

• Control Flow
  • core_python.ipynb
• Functions
  • functions.ipynb
• Statistics
  • summary_statistics.ipynb
  • Correlation & Correlation linear_regressions_and_simple_relationships.ipynb

Recordings

Title	Date	URL
Python Basics: Lists, Dictionaries, and More	2020-01-29	youtu.be/Mdi1dWzCIZE
Python Basics: Control Flow	2020-01-29	youtu.be/q1ZMx9p6dJo
Python Basics: Functions	2020-01-29	youtu.be/7pcILR2LtKo

Module 1 Section 04 - Python Libraries: NumPy and Pandas

• NumPy
  • intro_to_numpy.ipynb
  • (OPTIONAL EXTRA) math_with_tensors.ipynb
  • Activity: numpy_intro_activity.ipynb
• Pandas
  • from_numpy_to_pandas.ipynb

Recordings

Title	Date	URL
NumPy Intro	2020-02-05	youtu.be/Ea5tmWo0e5k
NumPy Activity	2020-02-05	youtu.be/ROiNq5WTjCc
From NumPy to Pandas	2020-02-05	youtu.be/Ng_TzUentmk

Module 1 Section 05 - Data Cleaning in Pandas

• Pandas & Data
  • from_numpy_to_pandas.ipynb
  • manipulating_data.ipynb
  • aggregation.ipynb
• Data Exploration & Cleaning
  • data_cleaning_with_pandas_overview.ipynb
  • exploring_data.ipynb

Recordings

Title	Date	URL
Brief Extra: Pandas & Loading Data	2020-02-05	youtu.be/-nr7bi7lVxQ
Data Exploration with Pandas	2020-02-11	youtu.be/W_ey_4uIGQ0
Data Exploration & Cleaning with Python	2020-02-11	youtu.be/KXNzYfWUoUM

Module 1 Section 06 - Data Visualization

• Data Visualization Intro
  • motivation.ipynb
  • how_to_use_visualizations.ipynb
• Good & Bad Visualizations
  • good_visualizations.ipynb
  • down_with_pie_chart.ipynb

Recordings

Title	Date	URL
Why Should I Visualize Data?	2020-02-11	youtu.be/AjEdgBRbvUU
Who Are Visualizations For?	2020-02-11	youtu.be/8t452nMFApc
Visualizations: The Good, The Bad & The Ugly	2020-02-12	youtu.be/yvwyvCt8qAI
Data Exploration Activity	2020-02-12	youtu.be/XPT6QgMbPos

Module 1 Section 07 - SQL and Relational Databases

• Introduction to SQL
  • sql_lesson.ipynb
  • intro_to_sql.ipynb
  • sql_exercises.ipynb
• More SQL
  • using_sql.ipynb
  • joins.ipynb
  • advanced_topics.ipynb

Recordings

Title	Date	URL
SQL & Realtional Databases Intro	2020-02-18	youtu.be/Ca-8RRZlLLo
Running SQL in Python	2020-02-18	youtu.be/IjF3bNF-eHc
More SQL & Joining Tables	2020-02-18	youtu.be/1PXDL-S71Cc
Creating and Updating SQL Databases	2020-02-18	youtu.be/c8Gyv_LXH8o
SQL & Execution Order	2020-02-19	youtu.be/NJEOpxZP9TI
SQL Subqueries	2020-02-19	youtu.be/mAEgY7BGlN8

Module 1 Section 08: Other Database structures

Recordings

Module 1 Section 09: JSON and APIs

• JSON
  • json_and_xml_intro.ipynb
• APIs
  • apis.ipynb
  • lifx_example.ipynb

Recordings

Title	Date	URL
JSON Data Format for Python	2020-02-19	youtu.be/EbCjd6OPdvg
APIs with Python	2020-02-19	youtu.be/NsfITpjTqAA
API Example with LIFX	2020-02-19	youtu.be/-zsoxAzkSLU

Module 1 Section 10: HTML, CSS, and Web Scraping

• HTML & CSS
  • html_css_intro.ipynb
• Web Scraping
  • web_scraping.ipynb
  • web_scraping_beautiful_soup_activity_00.ipynb {IN PROGRESS}

Recordings

Title	Date	URL
HTML and CSS Intro for Web Scraping	2020-02-26	youtu.be/MadMEVGMTUE
Intro & Ethics to Web Scraping	2020-02-26	youtu.be/ceH08GJlIOo
Web Scraping with Python & Beautiful Soup	2020-02-26	youtu.be/f6lj7xC0Y2g
Web Scraping Demo: Adventure Time	2020-02-26	youtu.be/v_a1qUuXd1Y

Module 1 Project: Movie Analysis

• Project Details
  • mod1_project_notes-pt_012120.ipynb
• Advice
  • general_advice.ipynb

Module 2

Module 2 Section 11 - Combinatorics and Probability

• Conditional Probability
  • probability_and_notation.ipynb
  • conditional_probability.ipynb
• Combinatorics
  • combinatorics.ipynb

Recordings

Title	Date	URL
Conditional Probability	2020-03-17	youtu.be/JDgm4Wqsvuw
Combinatorics	2020-03-17	youtu.be/hs5EFpUcTzw

Module 2 Section 12 - Statistical Distributions

• Statistical Distributions
  • statistical_distributions_intro.ipynb
  • statistical_distributions.ipynb
  • more_statistical_distributions.ipynb

Recordings

Title	Date	URL
Frequency Distributions & More Statistics	2020-03-19	youtu.be/bNUpLoDgLig
Review & Other Statistical Distributions	2020-03-24	youtu.be/YRor7gBV9Kw
Even More Statistical Distributions	2020-03-24	youtu.be/dVSnNHKyeAM

Module 2 Section 13 - Central Limit Theorem and Confidence Intervals

• Central Limit Theorem
  • sampling.ipynb
  • central_limit_theorem.ipynb
• Confidence Intervals
  • confidence_intervals.ipynb

Recordings

Title	Date	URL
Sampling	2020-03-24	youtu.be/x5KVX3ccbuc
Central Limit Theorem	2020-03-24	youtu.be/c2NDqWrCBno
Where Do Confidence Intervals Come From?	2020-03-26	youtu.be/jHLoLCCtumc

Module 2 Section 14 - Hypothesis Testing

• Experiment Design
  • experiment_design_intro.ipynb
  • hypothesis_testing_intro.ipynb
• Considerations
  • warnings.ipynb
  • multiple_comparisons.ipynb
• Statistical Tests
  • statistical_tests.ipynb
  • types_of_errors.ipynb
• t-Tests
  • t_distributions.ipynb
  • t_tests.ipynb

Recordings

Title	Date	URL
What Makes a Good Experiment?	2020-03-26	youtu.be/746no4_NvRM
Hypothesis Testing Intro	2020-03-26	youtu.be/TE8C-PsZfrw
Hypothesis Testing	2020-03-31	youtu.be/JnO5wKYnNfQ
The t-Distribution & t-Test	2020-03-31	youtu.be/8zey4ICieg0
Type 1 vs Type 2 Errors	2020-03-31	youtu.be/1IybE0mXWl4

Module 2 Section 15 - Statistical Power & ANOVA

• Parts of Hypothesis Tests
  • types_of_errors.ipynb
  • statistical_power.ipynb
  • effect_size.ipynb
• Welch's t-test & ANOVA
  • welchs_t_test.ipynb
  • multiple_comparisons.ipynb
  • anova.ipynb

Recordings

Title	Date	URL
Effect Size & Statistical Power Relationship	2020-03-31	youtu.be/0HtaoDgOF_A
Welch's t-Test vs Student's t-Test	2020-04-01	youtu.be/QNftsEYSwFA
Multiple Comparisons Warning	2020-04-07	youtu.be/voHPvSkX3f4
Introduction to ANOVA	2020-04-07	youtu.be/y1UWYQHw5Jo
Coding ANOVA: SciPy Method	2020-04-07	youtu.be/QnE8sBrKoNU
Coding ANOVA: Statsmodels OLS Method	2020-04-07	youtu.be/3cCM0lQFMM4

Module 2 Section 16 - A/B Testing

• A/B Testing
  • ab_testing.ipynb
  • ab_test_walkthrough.ipynb

Recordings

Title	Date	URL
A/B Testing	2020-04-07	youtu.be/2DVXuR-2LeA

Module 2 Section 17 - Bayesian Statistics

• Bayes' Theorem
  • bayes_theorem.ipynb

Recordings

Title	Date	URL
Bayesian Thinking	2020-04-21	[youtu.be/odZOxI_3BNI](https://youtu.be/odZOxI_3BNI]
Bayes' Theorem Coding Example: Testing Positive	2020-04-21	[youtu.be/yN7BPP25Bvg](https://youtu.be/yN7BPP25Bvg]
Visual of Bayes' Theorem	2020-04-21	[youtu.be/ib1a7c8MrtQ](https://youtu.be/ib1a7c8MrtQ]
Bayes' Theorem Followup: Testing Positive Twice	2020-04-21	[youtu.be/VgGUngEkYok](https://youtu.be/VgGUngEkYok]

Module 2 Section 18 - Introduction to Linear Regression

• Simple Linear Regression
  • linear_regressions_and_simple_relationships.ipynb

Recordings

Title	Date	URL
Intro to Linear Regression	2020-04-09	youtu.be/PBv749p-9yY

Module 2 Section 19 - Multiple Linear Regression

• Multiple Linear Regression
  • multiple_linear_regression.ipynb
  • multicollinearity.ipynb
  • model_validation.ipynb
  • linear_regression_example.ipynb

Recordings

Title	Date	URL
Multiple Linear Regression	2020-04-15	youtu.be/drbltsGcRNQ
Handling Categorical Variables	2020-04-15	youtu.be/57Cy58UnKv0
Dealing with Multicollinearity	2020-04-16	youtu.be/eGSG79vF6_E
Validating Models & k-Fold Cross-Validation	2020-04-16	youtu.be/nmIxCbv09G0

Module 2 Section 20 - Extensions to Linear Regression

• Polynomial & Interacting Terms
  • improving_linear_regression.ipynb

Recordings

Title	Date	URL
Extending Linear Regression: Polynomial & Interacting Terms	2020-04-22	[youtu.be/QbkwZ9cCb8I](https://youtu.be/QbkwZ9cCb8I]

---

Curriculum (v2.0)

Module 3

Module 3 Section 17 - Combinatorics

• probability_and_notation.ipynb
• conditional_probability.ipynb
• Permutations & Combinations
  • combinatorics.ipynb

Module 3 Section 18 - Statistical Distributions

• statistical_distributions_intro.ipynb
• statistical_distributions.ipynb

Module 3 Section 19 - Central Limit Theorem

• Central Limit Theorem
  • sampling-and-central-limit-theorem.ipynb
• Sampling Statistics
  • sampling-and-central-limit-theorem.ipynb
• Confidence Intervals
  • confidence-intervals.ipynb
  • t_distributions.ipynb

Module 3 Section 20 - Hypothesis Testing

• Intro to Experimental Design
  • experiment_design_intro.ipynb
• P-Values & Null Hypothesis
  • statistical_tests.ipynb
• Effect Sizes
  • effect_size.ipynb
• T-Tests
  • t_distributions.ipynb
  • t_tests.ipynb
• Type 1 & Type 2 Errors
  • types_of_errors.ipynb

Module 3 Section 21 - Statistical Power & ANOVA

• Statistical Power
  • statistical_power.ipynb
• Welch's T-Test
  • welchs_t_test.ipynb
• Multiple Comparisons & Goodhart's Law
  • warnings.ipynb
  • extras.ipynb
• ANOVA
  • anova.ipynb

Module 3 Section 22 - AB Testing

• A/B Testing
  • ab_testings.ipynb

Module 3 Section 23 - Bayesian Statistics

• Bayes Theorem
  • bayes_theorem.ipynb
• Naive Bayes
  • naive_bayes_classification.ipynb

Module 3 Section 24 - Resampling and Monte Carlo Simulation

• Data Generation
  • data_generation.ipynb
• Resampling
  • resampling.ipynb
• Monte Carlo
  • monte_carlo.ipynb
  • ultimate_hopscotch_simulation.ipynb

Module 4

Module 4 Section 25 - A Complete Data Science Project Using Multiple Regression

Module 4 Section 26 - Linear Algebra

• Linear Algebra Intro
  • intro_to_linear_algebra
• Math with Tensors
  • math_with_tensors.ipynb
• Solving With Linear Algebra
  • solving_with_linear_algebra.ipynb

Module 4 Section 27 - Calculus, Cost Function, and Gradient Descent

Derivatives - derivatives.ipynb

• Gradient Descent
  • gradient_descent.ipynb
• Gradient Descent Walkthrough
  • walkthrough_gradient_descent.ipynb

Module 4 Section 28 - Extensions to Linear Models

• Improving Linear Regression (Interactions & Polynomial)
  • improving_linear_regression.ipynb
• Regularization
  • regularization.ipynb
• Bias & Variance
  • bias_and_variance.ipynb

Module 4 Section 29 - Introduction to Logistic Regression

• Logistic Regression Intro
  • logistic_regression_intro.ipynb
• Logistic Regression
  • logistic_regression.ipynb
• Evaluation Metrics (Confusion Matrices)
  • evaluation_metrics.ipynb
• Evaluation Curves (ROC & AUC)
  • evaluation_curves.ipynb

Module 4 Section 30 - In-depth Logistic Regression

Module 4 Section 31 - Working with Time Series Data

• Time Series Intro
  • time_series_intro.ipynb
• Time Series Visualization
  • time_series_visualization.ipynb
• Time Series Trends
  • time_series_trends.ipynb

Module 4 Section 32 - Time Series Modeling

• Time Series Models Intro
  • time_series_models_basic.ipynb
• ARMA Model
  • time_series_model_arma.ipynb

Module 5

Module 5 Section 33 - K Nearest Neighbors

• Distance Metrics
  • distance_metrics.ipynb
• K Nearest Neighbors
  • k_nearest_neighbors.ipynb

Module 5 Section 34 - Decision Trees

• Decision Trees
  • decision_trees_intro.ipynb
  • information_to_make_decisions.ipynb
  • decision_tree_hyperparameters.ipynb
  • decision_tree_code_example.ipynb

Module 5 Section 35 - Ensemble Methods

• Ensemble Methods (Bagging, Random Forest, Adaboost, Gradient Boosting)
  • ensemble_methods.ipynb
  • bagging.ipynb
  • boosting.ipynb

Recordings

Title	Date	URL
Ensemble Machine Learning: Bagging & Boosting	2019-10-24	[youtu.be/xI-XdP2FLis](https://youtu.be/xI-XdP2FLis]
Machine Learning with Ensembles: Bagging & Boosting	2020-09-21	[youtu.be/nIYnh6uAun0](https://youtu.be/nIYnh6uAun0]
Ensemble Methods in Machine Learning: Bagging & Boosting	2019-11-08	[youtu.be/j1B1k1PZ8Wg](https://youtu.be/j1B1k1PZ8Wg]

Module 5 Section 36 - Support Vector Machines

• Support Vector Machine Intro
  • support_vector_machine_intro.ipynb
• Kernel Trick
  • kernel_trick.ipynb

Module 5 Section 37 - Principal Component Analysis

• Dimensionality
  • dimensionality.ipynb
• Principal Component Analysis
  • pca.ipynb
  • pca_example.ipynb

Module 5 Section 38 - Clustering

• K-means
  • k_means.ipynb
  • k_means_issues.ipynb
• Hierarchical Clustering
  • hierarchical_clustering.ipynb
• DBSCAN
  • dbscan.ipynb

Module 5 Section 39 - Building a Machine Learning Pipeline

• Pipelines
  • pipeline_intro.ipynb
• Grid Search
  • grid_search.ipynb

Recordings

Title	Date	URL
Machine Learning Pipelines	2019-11-14	youtu.be/SjeEM0r7RZo
Grid Search of Hyperparameters	2019-11-14	youtu.be/oi2NjZPQcmQ

Module 5 Section 40 - Big Data in PySpark

• Big Data Introduction
  • big_data_intro.ipynb
• Distributed Computing
  • distributed_parallel_computing.ipynb
  • tools_of_distributed_systems.ipynb
• MapReduce
  • map_reduce.ipynb
  • map_reduce_code.ipynb

Recordings

Title	Date	URL
Big Data & MapReduce	2019-11-12	youtu.be/LQVXvg1dL-8
Intro to Identifying & Handling Big Data	2019-08-15	youtu.be/tRd_hVTxk24
Intro to MapReduce	2019-08-15	youtu.be/2Amvm-BpCxg
MapReduce Coding Example	2019-08-15	youtu.be/AwsWrryp6tY

Module 5 Section 41 - Recommendation Systems

• Recommendation Systems
  • recommendation_systems_intro.ipynb
• Neighbor Memory Based Collab Filtering
  • neighbor_memory_based_collab_filtering.ipynb
• Matrix Factorization
  • matrix_factorization.ipynb

Recordings

Title	Date	URL
Recommendation Systems Intro	2019-11-15	youtu.be/lIIAEVxRl50
Neighbor-Based Collaboraitve Filtering	2019-11-15	youtu.be/pEOPyOCaoHw
Matrix Factorization & Embeddings	2019-11-15	youtu.be/olJKadbzdCQ
Embeddings Discussion	2019-11-15	youtu.be/V_6S4xw0JnQ
Recommendation Systems & Embeddings	2019-09-18	youtu.be/m1pj8hVnmn0

Module 6

Module 6 Section 42 - Graph Theory

• Graph Theory
  • graph_theory_basics.ipynb
  • paths.ipynb

Module 6 Section 43 - Foundations of Natural Language Processing

• NLP Introduction
  • intro_to_nlp.ipynb
  • text_processing.ipynb
  • feature_extraction.ipynb

Module 6 Section 44 - Introduction to Deep Learning

• Neural Networks
  • neural_networks.ipynb
  • activation_functions.ipynb
  • keras_implementation.ipynb

Module 6 Section 45 - Multi-Layer Perceptrons

• Neural Networks & Parts
  • neural_networks.ipynb
  • activation_functions.ipynb
  • keras_implementation.ipynb

Module 6 Section 46 - Tuning Neural Networks

• Overfitting
  • avoiding_overfitting.ipynb
• Optimization
  • optimizations.ipynb

Moduel Section 49 - Deep NLP - Word Embeddings

• Word Embeddings
  • embeddings.ipynb