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Data Scientist in 10 Weeks

Week 1 - Getting Started With Python

Welcome to Data Scientist in 10 Weeks! (1:27)
Installing Prerequisites (6:03)
Installing Python and Pygame Windows OS (5:16)
Printing To The Screen (7:46)
Strings (9:45)
Variables (11:25)
Practice Exercises: Variables And Strings
Operations On String (16:01)
Practice Exercises: Operations On Strings
Ints And Floats (7:55)
Operations On Ints And Floats (12:26)
Practice Exercise: Arithmetic Operations
Booleans (4:35)
Boolean Expressions (12:52)
Type Casting (12:39)
Functions (12:58)
Practice Exercises: Functions
For Loops (10:17)
While Loops (8:06)
Review Question: Indentations
Breaking and Continuing Loops (6:13)
Exercise Sheet Break and Continue
Importing Modules (13:50)
Review Question: Modules
Tuples (12:23)
Operations On Tuples (14:20)
Writing The Skeleton Of PyGame Part 1 (14:52)
If Statements (19:50)
Practice Exercises: If Statements
Writing The Skeleton Of PyGame Part 2 (17:16)
File Output (17:38)
File Input (14:03)
File Position (12:44)
Additional Python Exercises Intro (0:21)
Additional Exercises Exercise 1 Sample Solutions (2:37)
Additional Exercises Exercise 2 Sample Solutions (7:48)
Additional Exercises Exercise 3 Sample Solutions (7:09)
Additional Exercises Exercise 4 Sample Solutions (9:53)
Additional Exercises Exercise 5 Sample Solutions (5:10)

Week 2 - Making a complex and interactive Program

Images In PyGame (8:50)
Alphas And Rotating Images (15:33)
Cropping Images (14:21)
Adding The Other Goal Parts (12:43)
Moving The Images To The Right Location (12:01)
Lists (19:58)
Dictionary (12:24)
Practice Exercises: Dictionaries
Processing Pressed Keys And Pass Statement (9:24)
Defining Default Values And FPS (9:48)
The Move Function (16:02)
Implementing The Player Movement (13:27)
Updating The Image On The Screen (9:00)
Global Variables (5:08)
Update Function (6:37)
Making The Player Run At The Ball (10:47)
The Kicking Motion (21:00)
Shooting The Ball (9:21)
A First Look At Classes (14:13)
Methods In Classes (14:12)
Class Inheritance (13:53)
Creating The Game Class (7:13)
Creating The Background Class (16:47)
Creating The Ball Class (11:57)
Creating The Player Class (18:43)
Implementing The New Classes Part 1 (14:20)
Implementing The New Classes Part 2 (7:12)
Fixing The Remaining Bugs From Class Implementation (7:24)
Resetting The Player And The Ball (6:28)
Creating The Target Class (20:42)
Implementing The Target (10:57)
Adding Score To A Class (7:15)
Implementing The Score In Our Game (3:01)
User Input (8:20)
Review Question: User Input

Week 3 - Getting Started With Data Visualization

Introduction to Matplotlib and Installing Anaconda (5:36)
Making a Scatter Plot (18:37)
Understanding Figures (8:34)
Creating Axes (12:35)
Making a Line Plot (13:41)
Data Visualization Exercise Sheet 1 (0:23)
Reading the Data From Txt File (8:20)
Reading the Data From CSV File (11:00)
Data Visualization Sheet 1 Exercise 1 Solution (7:30)
Data Visualization Sheet 1 Exercise 2 Solution (8:34)
Customization Foreword (0:52)
Changing the x and y limits (6:41)
Adding a Title and Axis Labels (9:06)
Adding in Equations into Text (2:42)
Adding and Formatting Axis Ticks (12:18)
Customizing Tick Labels (10:59)
Data Visualization Exercise Sheet 2 (0:37)
Data Visualization Sheet 2 Exercise 1 Solution (11:58)
Data Visualization Sheet 2 Exercise 2 Solution (16:32)
Adding a Legend (6:24)
Adding Text Annotations (11:29)
Customizing our Graph Edges (8:02)
Using Plot Styles (4:15)
Saving Our Plots (6:55)
Data Visualization Exercise Sheet 3 (0:55)
Data Visualization Sheet 3 Datetime Intro (13:29)
Data Visualization Sheet 3 Exercise 1 Solution (8:36)
Data Visualization Sheet 3 Exercise 2 Solution Part 1 (12:53)
Data Visualization Sheet 3 Exercise 2 Solution Part 2 (16:37)
Data Visualization Sheet 3 Exercise 2 Solution Part 3 (20:53)
Data Visualization Sheet 3 Exercise 3 Solution (13:44)

Week 4 - Advanced Data Visualization and Essential Plotting Techniques

Histograms (14:23)
Advanced Histograms and Patches (14:02)
Bar Graphs (11:30)
Error Bars on Bar Graphs (6:01)
Box and Whisker Plots (9:53)
Pie Charts (12:41)
2-Dimensional Histograms (9:12)
Data Visualization Exercise Sheet 4 (0:40)
Data Visualization Sheet 4 Exercise 1 Sample Solution (16:13)
Data Visualization Sheet 4 Exercise 2 Sample Solution (13:52)
Data Visualization Sheet 4 Exercise 3 Sample Solution (17:28)
Data Visualization Sheet 4 Exercise 4 Sample Solution (10:15)
Data Visualization Sheet 4 Exercise 5 Sample Solution (12:49)
Loading and Showing Images (10:26)
Colormaps (17:56)
Adding a colorbar to our Axis (11:00)
Data Visualization Exercise Sheet 5 (0:28)
Data Visualization Sheet 5 Exercise 1 Sample Solution (4:28)
Data Visualization Sheet 5 Exercise 2 Sample Solution Part 1 (10:52)
Data Visualization Sheet 5 Exercise 2 Sample Solution Part 2 (12:37)
3D Line and Scatter Plots (10:28)
Changing View Angles and Animating our Graphs (10:23)
Data Visualization Exercise Sheet 6 Intro (0:16)
Data Visualization Sheet 6 Exercise 1 Sample Solution (15:27)

Week 5 - Applied Data Analysis

Course Outline (0:53)
Installing NumPy (1:58)
The NumPy Array (10:51)
Advantages of the NumPy Array (8:56)
Getting Pandas (1:37)
Creating a DataFrame (14:33)
Indexing and Printing (5:55)
Modyfing Indices (8:45)
The Series Data Structure (6:48)
Data Analysis Exercise Sheet 1 Intro (0:24)
Data Analysis Sheet 1 Exercise 1 Sample Solution (10:14)
Data Analysis Sheet 1 Exercise 2 Sample Solution (4:28)
Saving our data to a CSV (16:21)
Reading Data from a CSV (14:45)
Missing Values and Saving (4:15)
Extra Options for Reading Data from CSV (6:01)
Data Analysis Exercise Sheet 2 Intro (0:25)
Data Analysis Sheet 2 Exercise 1 Sample Solution (4:59)
Data Analysis Sheet 2 Exercise 2 Sample Solution (2:09)
Navigating the DataFrame (13:12)
Setting Values and Taking Subsets of Our DataFrame (10:16)
Navigation Using iloc (7:57)
Getting the Names of the Columns in Our DataFrame (3:33)
Deleting Columns (3:43)
Iterating Over Our DataFrame (6:03)
Creating a New Column (8:36)
Data Analysis Exercise Sheet 3 Intro (0:27)
Data Analysis Sheet 3 Exercise 1 Sample Solution (9:05)
Data Analysis Sheet 3 Exercise 2 Sample Solution (9:30)

Week 6 - Advanced Data Analysis and Dealing with Real World Data

Sorting (12:13)
Filtering For Specific Values (9:18)
Advanced Filter For Specific Values (10:12)
Counting Unique Occurrences (9:18)
Mapping Series Data (7:46)
Accessing and Using the Unique Occurrence Values (8:54)
Applying Functions Onto our DataFrame (11:30)
Data Analysis Exercise Sheet 4 Intro (0:29)
Statistical Overview of our DataFrame (9:37)
Data Analysis Sheet 4 Exercise 1 Sample Solution Part 1 (17:33)
Data Analysis Sheet 4 Exercise 1 Sample Solution Part 2 (19:59)
Data Analysis Sheet 4 Exercise 1 Sample Solution Part 3 (12:57)
Calculating Specific Statistical Values (6:36)
Calculating the Covariance and Correlation for the Data in our DataFrame (7:52)
Dropping Duplicate Rows (5:22)
Data Analysis Exercise Sheet 5 Intro (0:16)
Data Analysis Exercise Sheet 5 Exercise 1 Sample Solution (4:18)
Data Analysis Exercise Sheet 5 Exercise 2 Sample Solution (16:10)
Data Analysis Exercise Sheet 5 Exercise 3 Sample Solution (14:44)
Understanding Missing Data (8:07)
Checking for Missing Data (7:07)
Filling in Missing Data (13:39)
Dropping Missing Data (12:36)
Filling Missing Data through Interpolation (13:16)
Data Analysis Exercise Sheet 6 Intro (0:16)
Data Analysis Exercise Sheet 6 Exercise 1 Sample Solution (6:52)
Replacing Values (7:37)
Concatenating DataFrames (10:45)
Creating Pivot Tables (9:00)
Data Analysis Exercise Sheet 7 Intro (0:11)
Data Analysis Exercise Sheet 7 Exercise 1 Sample Solution (6:15)

Week 7 - SQL in Python

SQL Intro (4:40)
Data Types (5:16)
Creating and Connecting to a DB (4:53)
Creating and Removing Tables (11:20)
Inserting Data (8:09)
Reading Data (10:17)
Exercise Sheet 1 Intro (0:28)
Sheet 1 Exercise 1 Solutions Part 1 (11:18)
Sheet 1 Exercise 1 Solutions Part 2 (6:48)
Sheet 1 Exercise 2 Solutions (8:08)
Sheet 1 Exercise 3 Solutions (4:53)
Aliasing and Ordering (16:29)
Conditional Searches Direct Comparison (9:26)
Conditional Searches Group Comparison (17:13)
Joining Conditions (6:10)
Negating Conditionals (5:08)
Creating New Columns and Arithmetics (8:54)
Exercise Sheet 2 Intro (0:35)
Exercise Sheet 2 Exercise 1 Solutions (7:48)
Exercise Sheet 2 Exercise 2 Solutions (9:07)
Data Type Conversions (5:52)
Manipulating Strings (13:27)
String Positional Information (6:27)
String Replacements Subsets And Concatinations (10:43)
Dates And Times (16:55)
Date And Time Intervals (15:39)
Exercise Sheet 3 Intro (0:50)
Exercise Sheet 3 Exercise 1 Solutions (14:07)
Exercise Sheet 3 Exercise 2 Solutions (13:40)
Aggregation Functions (8:42)
Grouping And Conditional Grouping (9:14)
Logic Statements (10:42)
Comments (7:14)
Exercise Sheet 4 Intro (0:28)
Exercise Sheet 4 Exercise 1 Solutions (10:29)
Inner Joins (9:30)
Left Right And Full Joins (10:14)
Self Joins And Multiple Conditions (7:31)
Union (7:10)
Subqueries (9:44)
Window Functions (12:03)
Row Counting Window Functions (8:14)
Using Other Rows With Window Functions (8:36)
NTiles And Window Function Aliases (9:05)
Evaluating Performance (5:04)
Replacing Null Values (7:50)
Exercise Sheet 5 Intro (0:19)
Exercise Sheet 5 Exercise 1 Solutions (9:17)
Exercise Sheet 5 Exercise 2 Solutions (5:50)
Exercise Sheet 5 Exercise 3 Solutions (6:02)

Week 8 - Scrapping data from static websites

Introduction (3:20)
Prerequisite Libraries (3:00)
Introduction to The Modulus Operation (5:01)
Introduction to Simple Error Handling (4:25)
Response Status Codes From a HTTP Request (7:18)
Error codes
Reading The Response Text From Our Request (11:40)
First Approach at Parsing The Data (13:18)
Understanding the Exception Cases (6:39)
Parsing Out All Data for One Company (9:33)
Determining Where We Can Get More Ticker Symbols (15:46)
Extracting Company Ticker Symbols Part 1 (16:32)
Extracting Company Ticker Symbols Part 2 (10:41)
Extracting Out Ticker Symbols
Getting Data For All Parsed Companies (8:11)
Final Data For All Parsed Companies (5:13)
Final Result (1:40)
Your Own Web Scrap

Week 9 - Scrapping data from dynamic websites

Prerequisite Libraries (5:02)
Short review: Recursive Functions (7:43)
Update For Webdriver To Use (2:28)
Getting started with Selenium (8:47)
View The Page Source (9:14)
Website Elements and XPath (8:11)
Navigating Deeper Into The Page Source (14:37)
Identifying The Path To Our Data (19:28)
Using The XPath To Our Data (9:50)
Parsing Out Our Data (8:42)
Getting Our Final Data (14:56)
Final Results (4:13)
Scraping a website that uses AJAX to generate content
Adding Text Into A Form (19:35)
Pressing Buttons And Navigating On Site Pop-Ups (19:35)

Week 10 - Your Final Project

Your Portfolio Project (6:59)

Bonus: Portfolio and Email Pitch

How to Build a Portfolio Item (14:45)
Email Pitch Template

Bonus: GitHub

What is GitHub? (5:13)
Why You Need to Be Using GitHub (11:59)
Setting Up You First GitHub Project (11:12)
Finalizing Your First GitHub Project (21:57)

Bonus: Kaggle

What is Kaggle? (8:06)
Why You Need to Be Using Kaggle (7:37)
How to Create Your First Kaggle Project (19:15)

Bonus: Data Science Interview Questions

Data Science interview Questions Intro (12:39)
General Data Science Interview Questions Part 1 (14:57)
General Data Science Interview Questions Part 2 (16:50)
General Data Science Interview Questions Part 3 (17:33)
Technical Data Science Interview Questions Part 1 (18:21)

Bonus: An Introduction to Numpy

Numpy Introduction (2:52)
Creating Numpy Arrays (10:17)
Array Properties (12:15)
Numpy Array Operations (7:45)
Random Numbers (14:51)
Modifying Numpy Arrays (9:40)
Vectorization (9:12)
Multi-dimensional Arrays (9:19)
Indexing Multi-dimensional Arrays (7:18)
Copies (6:06)
Mathematical Operations (6:02)

Bonus: Introduction To Statistical Principles

Introduction and Samples (18:50)
Outliers and Standard Error (14:50)
Statistical Significance p-value (11:27)
Statistical Significance t-statistic (14:17)
Inferences from Data Correlation Coefficient (13:32)
Causation, Correlation, Signal, and Noise (13:15)

Bonus: How To Build Models

Intro to Building Models (6:14)
How to Build Models (8:13)
Types of Models (7:44)
Model Building Example Part 1 (11:43)
Model Building Example Part 2 (14:35)

Bonus: Introduction to APIs

APIs Introduction (10:10)
API Examples (17:42)
API Practice Example (22:14)

Bonus: Real World Application of Social Media API

Getting your Twitter Credentials for Authentication (2:42)
Twitter Time Limitations (3:16)
Sending Your First Request to the Twitter API (13:35)
Dealing with Data in the Response (16:25)
Getting Tweets from a Specific Time (11:03)
Getting All Tweets by Moving Backwards in Time (17:41)
Filtering for English Tweets and Picking Out Keywords (12:33)
Identifying Relevant Tweets and Keeping Track of Data (15:43)
Setting Up for Plotting the Mined Data from Twitter (16:47)
Adjusting the Maximum Time and Adding Ticks to Our Graph (10:21)
Analyzing the Relevant Data (11:11)
Streaming Live Twitter Data and Outlook for the Next Steps (14:13)

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