Week 1 - Getting Started With Python
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Welcome to Data Scientist in 10 Weeks! (1:27)
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Installing Prerequisites (6:03)
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Installing Python and Pygame Windows OS (5:16)
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Printing To The Screen (7:46)
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Strings (9:45)
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Variables (11:25)
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Practice Exercises: Variables And Strings
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Operations On String (16:01)
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Practice Exercises: Operations On Strings
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Ints And Floats (7:55)
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Operations On Ints And Floats (12:26)
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Practice Exercise: Arithmetic Operations
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Booleans (4:35)
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Boolean Expressions (12:52)
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Type Casting (12:39)
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Functions (12:58)
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Practice Exercises: Functions
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For Loops (10:17)
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While Loops (8:06)
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Review Question: Indentations
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Breaking and Continuing Loops (6:13)
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Exercise Sheet Break and Continue
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Importing Modules (13:50)
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Review Question: Modules
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Tuples (12:23)
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Operations On Tuples (14:20)
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Writing The Skeleton Of PyGame Part 1 (14:52)
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If Statements (19:50)
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Practice Exercises: If Statements
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Writing The Skeleton Of PyGame Part 2 (17:16)
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File Output (17:38)
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File Input (14:03)
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File Position (12:44)
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Additional Python Exercises Intro (0:21)
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Additional Exercises Exercise 1 Sample Solutions (2:37)
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Additional Exercises Exercise 2 Sample Solutions (7:48)
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Additional Exercises Exercise 3 Sample Solutions (7:09)
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Additional Exercises Exercise 4 Sample Solutions (9:53)
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Additional Exercises Exercise 5 Sample Solutions (5:10)
Week 2 - Making a complex and interactive Program
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Images In PyGame (8:50)
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Alphas And Rotating Images (15:33)
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Cropping Images (14:21)
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Adding The Other Goal Parts (12:43)
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Moving The Images To The Right Location (12:01)
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Lists (19:58)
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Dictionary (12:24)
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Practice Exercises: Dictionaries
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Processing Pressed Keys And Pass Statement (9:24)
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Defining Default Values And FPS (9:48)
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The Move Function (16:02)
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Implementing The Player Movement (13:27)
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Updating The Image On The Screen (9:00)
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Global Variables (5:08)
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Update Function (6:37)
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Making The Player Run At The Ball (10:47)
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The Kicking Motion (21:00)
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Shooting The Ball (9:21)
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A First Look At Classes (14:13)
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Methods In Classes (14:12)
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Class Inheritance (13:53)
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Creating The Game Class (7:13)
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Creating The Background Class (16:47)
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Creating The Ball Class (11:57)
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Creating The Player Class (18:43)
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Implementing The New Classes Part 1 (14:20)
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Implementing The New Classes Part 2 (7:12)
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Fixing The Remaining Bugs From Class Implementation (7:24)
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Resetting The Player And The Ball (6:28)
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Creating The Target Class (20:42)
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Implementing The Target (10:57)
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Adding Score To A Class (7:15)
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Implementing The Score In Our Game (3:01)
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User Input (8:20)
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Review Question: User Input
Week 3 - Getting Started With Data Visualization
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Introduction to Matplotlib and Installing Anaconda (5:36)
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Making a Scatter Plot (18:37)
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Understanding Figures (8:34)
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Creating Axes (12:35)
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Making a Line Plot (13:41)
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Data Visualization Exercise Sheet 1 (0:23)
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Reading the Data From Txt File (8:20)
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Reading the Data From CSV File (11:00)
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Data Visualization Sheet 1 Exercise 1 Solution (7:30)
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Data Visualization Sheet 1 Exercise 2 Solution (8:34)
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Customization Foreword (0:52)
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Changing the x and y limits (6:41)
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Adding a Title and Axis Labels (9:06)
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Adding in Equations into Text (2:42)
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Adding and Formatting Axis Ticks (12:18)
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Customizing Tick Labels (10:59)
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Data Visualization Exercise Sheet 2 (0:37)
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Data Visualization Sheet 2 Exercise 1 Solution (11:58)
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Data Visualization Sheet 2 Exercise 2 Solution (16:32)
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Adding a Legend (6:24)
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Adding Text Annotations (11:29)
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Customizing our Graph Edges (8:02)
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Using Plot Styles (4:15)
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Saving Our Plots (6:55)
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Data Visualization Exercise Sheet 3 (0:55)
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Data Visualization Sheet 3 Datetime Intro (13:29)
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Data Visualization Sheet 3 Exercise 1 Solution (8:36)
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Data Visualization Sheet 3 Exercise 2 Solution Part 1 (12:53)
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Data Visualization Sheet 3 Exercise 2 Solution Part 2 (16:37)
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Data Visualization Sheet 3 Exercise 2 Solution Part 3 (20:53)
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Data Visualization Sheet 3 Exercise 3 Solution (13:44)
Week 4 - Advanced Data Visualization and Essential Plotting Techniques
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Histograms (14:23)
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Advanced Histograms and Patches (14:02)
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Bar Graphs (11:30)
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Error Bars on Bar Graphs (6:01)
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Box and Whisker Plots (9:53)
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Pie Charts (12:41)
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2-Dimensional Histograms (9:12)
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Data Visualization Exercise Sheet 4 (0:40)
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Data Visualization Sheet 4 Exercise 1 Sample Solution (16:13)
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Data Visualization Sheet 4 Exercise 2 Sample Solution (13:52)
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Data Visualization Sheet 4 Exercise 3 Sample Solution (17:28)
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Data Visualization Sheet 4 Exercise 4 Sample Solution (10:15)
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Data Visualization Sheet 4 Exercise 5 Sample Solution (12:49)
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Loading and Showing Images (10:26)
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Colormaps (17:56)
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Adding a colorbar to our Axis (11:00)
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Data Visualization Exercise Sheet 5 (0:28)
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Data Visualization Sheet 5 Exercise 1 Sample Solution (4:28)
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Data Visualization Sheet 5 Exercise 2 Sample Solution Part 1 (10:52)
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Data Visualization Sheet 5 Exercise 2 Sample Solution Part 2 (12:37)
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3D Line and Scatter Plots (10:28)
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Changing View Angles and Animating our Graphs (10:23)
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Data Visualization Exercise Sheet 6 Intro (0:16)
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Data Visualization Sheet 6 Exercise 1 Sample Solution (15:27)
Week 5 - Applied Data Analysis
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Course Outline (0:53)
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Installing NumPy (1:58)
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The NumPy Array (10:51)
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Advantages of the NumPy Array (8:56)
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Getting Pandas (1:37)
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Creating a DataFrame (14:33)
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Indexing and Printing (5:55)
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Modyfing Indices (8:45)
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The Series Data Structure (6:48)
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Data Analysis Exercise Sheet 1 Intro (0:24)
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Data Analysis Sheet 1 Exercise 1 Sample Solution (10:14)
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Data Analysis Sheet 1 Exercise 2 Sample Solution (4:28)
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Saving our data to a CSV (16:21)
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Reading Data from a CSV (14:45)
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Missing Values and Saving (4:15)
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Extra Options for Reading Data from CSV (6:01)
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Data Analysis Exercise Sheet 2 Intro (0:25)
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Data Analysis Sheet 2 Exercise 1 Sample Solution (4:59)
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Data Analysis Sheet 2 Exercise 2 Sample Solution (2:09)
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Navigating the DataFrame (13:12)
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Setting Values and Taking Subsets of Our DataFrame (10:16)
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Navigation Using iloc (7:57)
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Getting the Names of the Columns in Our DataFrame (3:33)
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Deleting Columns (3:43)
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Iterating Over Our DataFrame (6:03)
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Creating a New Column (8:36)
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Data Analysis Exercise Sheet 3 Intro (0:27)
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Data Analysis Sheet 3 Exercise 1 Sample Solution (9:05)
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Data Analysis Sheet 3 Exercise 2 Sample Solution (9:30)
Week 6 - Advanced Data Analysis and Dealing with Real World Data
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Sorting (12:13)
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Filtering For Specific Values (9:18)
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Advanced Filter For Specific Values (10:12)
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Counting Unique Occurrences (9:18)
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Mapping Series Data (7:46)
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Accessing and Using the Unique Occurrence Values (8:54)
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Applying Functions Onto our DataFrame (11:30)
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Data Analysis Exercise Sheet 4 Intro (0:29)
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Statistical Overview of our DataFrame (9:37)
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Data Analysis Sheet 4 Exercise 1 Sample Solution Part 1 (17:33)
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Data Analysis Sheet 4 Exercise 1 Sample Solution Part 2 (19:59)
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Data Analysis Sheet 4 Exercise 1 Sample Solution Part 3 (12:57)
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Calculating Specific Statistical Values (6:36)
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Calculating the Covariance and Correlation for the Data in our DataFrame (7:52)
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Dropping Duplicate Rows (5:22)
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Data Analysis Exercise Sheet 5 Intro (0:16)
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Data Analysis Exercise Sheet 5 Exercise 1 Sample Solution (4:18)
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Data Analysis Exercise Sheet 5 Exercise 2 Sample Solution (16:10)
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Data Analysis Exercise Sheet 5 Exercise 3 Sample Solution (14:44)
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Understanding Missing Data (8:07)
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Checking for Missing Data (7:07)
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Filling in Missing Data (13:39)
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Dropping Missing Data (12:36)
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Filling Missing Data through Interpolation (13:16)
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Data Analysis Exercise Sheet 6 Intro (0:16)
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Data Analysis Exercise Sheet 6 Exercise 1 Sample Solution (6:52)
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Replacing Values (7:37)
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Concatenating DataFrames (10:45)
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Creating Pivot Tables (9:00)
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Data Analysis Exercise Sheet 7 Intro (0:11)
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Data Analysis Exercise Sheet 7 Exercise 1 Sample Solution (6:15)
Week 7 - SQL in Python
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SQL Intro (4:40)
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Data Types (5:16)
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Creating and Connecting to a DB (4:53)
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Creating and Removing Tables (11:20)
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Inserting Data (8:09)
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Reading Data (10:17)
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Exercise Sheet 1 Intro (0:28)
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Sheet 1 Exercise 1 Solutions Part 1 (11:18)
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Sheet 1 Exercise 1 Solutions Part 2 (6:48)
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Sheet 1 Exercise 2 Solutions (8:08)
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Sheet 1 Exercise 3 Solutions (4:53)
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Aliasing and Ordering (16:29)
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Conditional Searches Direct Comparison (9:26)
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Conditional Searches Group Comparison (17:13)
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Joining Conditions (6:10)
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Negating Conditionals (5:08)
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Creating New Columns and Arithmetics (8:54)
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Exercise Sheet 2 Intro (0:35)
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Exercise Sheet 2 Exercise 1 Solutions (7:48)
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Exercise Sheet 2 Exercise 2 Solutions (9:07)
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Data Type Conversions (5:52)
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Manipulating Strings (13:27)
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String Positional Information (6:27)
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String Replacements Subsets And Concatinations (10:43)
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Dates And Times (16:55)
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Date And Time Intervals (15:39)
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Exercise Sheet 3 Intro (0:50)
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Exercise Sheet 3 Exercise 1 Solutions (14:07)
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Exercise Sheet 3 Exercise 2 Solutions (13:40)
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Aggregation Functions (8:42)
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Grouping And Conditional Grouping (9:14)
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Logic Statements (10:42)
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Comments (7:14)
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Exercise Sheet 4 Intro (0:28)
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Exercise Sheet 4 Exercise 1 Solutions (10:29)
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Inner Joins (9:30)
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Left Right And Full Joins (10:14)
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Self Joins And Multiple Conditions (7:31)
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Union (7:10)
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Subqueries (9:44)
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Window Functions (12:03)
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Row Counting Window Functions (8:14)
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Using Other Rows With Window Functions (8:36)
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NTiles And Window Function Aliases (9:05)
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Evaluating Performance (5:04)
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Replacing Null Values (7:50)
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Exercise Sheet 5 Intro (0:19)
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Exercise Sheet 5 Exercise 1 Solutions (9:17)
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Exercise Sheet 5 Exercise 2 Solutions (5:50)
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Exercise Sheet 5 Exercise 3 Solutions (6:02)
Week 8 - Scrapping data from static websites
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Introduction (3:20)
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Prerequisite Libraries (3:00)
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Introduction to The Modulus Operation (5:01)
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Introduction to Simple Error Handling (4:25)
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Response Status Codes From a HTTP Request (7:18)
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Error codes
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Reading The Response Text From Our Request (11:40)
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First Approach at Parsing The Data (13:18)
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Understanding the Exception Cases (6:39)
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Parsing Out All Data for One Company (9:33)
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Determining Where We Can Get More Ticker Symbols (15:46)
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Extracting Company Ticker Symbols Part 1 (16:32)
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Extracting Company Ticker Symbols Part 2 (10:41)
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Extracting Out Ticker Symbols
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Getting Data For All Parsed Companies (8:11)
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Final Data For All Parsed Companies (5:13)
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Final Result (1:40)
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Your Own Web Scrap
Week 9 - Scrapping data from dynamic websites
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Prerequisite Libraries (5:02)
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Short review: Recursive Functions (7:43)
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Update For Webdriver To Use (2:28)
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Getting started with Selenium (8:47)
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View The Page Source (9:14)
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Website Elements and XPath (8:11)
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Navigating Deeper Into The Page Source (14:37)
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Identifying The Path To Our Data (19:28)
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Using The XPath To Our Data (9:50)
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Parsing Out Our Data (8:42)
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Getting Our Final Data (14:56)
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Final Results (4:13)
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Scraping a website that uses AJAX to generate content
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Adding Text Into A Form (19:35)
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Pressing Buttons And Navigating On Site Pop-Ups (19:35)
Week 10 - Your Final Project
Bonus: Portfolio and Email Pitch
Bonus: GitHub
Bonus: Kaggle
Bonus: Data Science Interview Questions
Bonus: An Introduction to Numpy
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Numpy Introduction (2:52)
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Creating Numpy Arrays (10:17)
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Array Properties (12:15)
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Numpy Array Operations (7:45)
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Random Numbers (14:51)
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Modifying Numpy Arrays (9:40)
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Vectorization (9:12)
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Multi-dimensional Arrays (9:19)
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Indexing Multi-dimensional Arrays (7:18)
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Copies (6:06)
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Mathematical Operations (6:02)
Bonus: Introduction To Statistical Principles
Bonus: How To Build Models
Bonus: Introduction to APIs
Bonus: Real World Application of Social Media API
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Getting your Twitter Credentials for Authentication (2:42)
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Twitter Time Limitations (3:16)
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Sending Your First Request to the Twitter API (13:35)
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Dealing with Data in the Response (16:25)
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Getting Tweets from a Specific Time (11:03)
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Getting All Tweets by Moving Backwards in Time (17:41)
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Filtering for English Tweets and Picking Out Keywords (12:33)
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Identifying Relevant Tweets and Keeping Track of Data (15:43)
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Setting Up for Plotting the Mined Data from Twitter (16:47)
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Adjusting the Maximum Time and Adding Ticks to Our Graph (10:21)
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Analyzing the Relevant Data (11:11)
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Streaming Live Twitter Data and Outlook for the Next Steps (14:13)
