Categories

There are currently no items in your shopping cart.

User Panel

Forgot your password?.

Data Science Fundamentals Part 1: Learning Basic Concepts – Data Wrangling – and Databases with Python

Introduction
Data Science Fundamentals Part 1: Introduction 00:07:00


Lesson 1: Introduction to Data Science with Python
Topics 00:01:37
1.1 Welcome to the Course 00:03:14
1.2 Why Data Science and Why Now? 00:07:48
1.3 The Potential of Data Science 00:24:21
1.4 Getting Set Up with a Data Science Development Environment 00:07:41
1.5 A Python (3) Primer 00:22:33
1.6 Python for Data Science 00:14:59
1.7 What’s to Come 00:10:10


Lesson 2: The Data Science Process—Building Your First Application
Topics 00:01:17
2.1 Introduction to the Data Science Process 00:07:17
2.2 Defining Your Problem 00:06:46
2.3 Acquiring Data 00:21:03
2.4 Wrangling Data 00:28:05
2.5 Exploring Data 00:28:48
2.6 The Simplest Recommender—Triangle Closing 00:21:29
2.7 Triadic Closure in Python, Part 1 00:25:24
2.7 Triadic Closure in Python, Part 2 00:27:36
2.8 Evaluate Results, Part 1 00:11:05
2.8 Evaluate Results, Part 2 00:18:37
2.8 Evaluate Results, Part 3 00:18:30
2.9 Present and Disseminate 00:16:32
2.10 The Data Science Process Applied: Cheaper Beds, Better Breakfasts 00:06:27


Lesson 3: Acquiring Data—Sources and Methods
Topics 00:01:41
3.1 The Data Science Mindset, Part 1 00:14:56
3.1 The Data Science Mindset, Part 2 00:15:34
3.2 Where to Get Data—Sources and Services 00:16:46
3.3 How the Web Works, Part 1 00:19:54
3.3 How the Web Works, Part 2 00:14:32
3.4 Downloading and Parsing Data with Python, Part 1 00:09:25
3.4 Downloading and Parsing Data with Python, Part 2 00:28:12
3.4 Downloading and Parsing Data with Python, Part 3 00:15:25
3.5 Working with APIs, Part 1 00:13:44
3.5 Working with APIs, Part 2 00:10:43
3.5 Working with APIs, Part 3 00:28:16
3.6 Data Blending—Downloading Venues from Foursquare, Part 1 00:13:58
3.6 Data Blending—Downloading Venues from Foursquare, Part 2 00:22:24


Lesson 4: Adding Structure—Parsing Data and Data Models
Topics 00:01:13
4.1 Ideas and Implementations 00:11:59
4.2 Data Models—Adding Structure to Data 00:23:56
4.3 Building Abstractions—Object-Oriented Programming, Part 1 00:11:47
4.3 Building Abstractions—Object-Oriented Programming, Part 2 00:19:46
4.4 A Brief Pythonic Diversion—Classes, Part 1 00:21:30
4.4 A Brief Pythonic Diversion—Classes, Part 2 00:14:29
4.4 A Brief Pythonic Diversion—Classes, Part 3 00:11:00
4.5 The Case for (and against) OOP, Part 1 00:23:37
4.5 The Case for (and against) OOP, Part 2 00:22:01
4.5 The Case for (and against) OOP, Part 3 00:15:15
4.5 The Case for (and against) OOP, Part 4 00:14:25
4.5 The Case for (and against) OOP, Part 5 00:29:01
4.5 The Case for (and against) OOP, Part 6 00:20:45
4.5 The Case for (and against) OOP, Part 7 00:13:04


Lesson 5: Storing Data—Persistence with Relational Databases
Topics 00:01:20
5.1 Data Models Applied—Relational Databases with SQLite, Part 1 00:26:56
5.1 Data Models Applied—Relational Databases with SQLite, Part 2 00:25:58
5.2 What’s in a Schema—Mapping Data Models to Data Tables 00:23:10
5.3 Querying Data(bases)—Thinking Relationally, Part 1 00:06:36
5.4 Querying Data(bases)—Thinking Relationally, Part 2 00:19:43
5.5 Querying Data(bases)—Thinking Relationally, Part 3 00:25:31
5.6 Querying Data(bases)—Thinking Relationally, Part 4 00:09:18
5.7 ORMs versus SQL 00:04:52
5.8 Extract, Transform, Load—Putting It All Together 00:10:11


Lesson 6: Validating Data—Provenance and Quality Control
Topics 00:01:21
6.1 A Brief Historical Diversion 00:10:42
6.2 Defensive Data Analysis—Quality Checks 00:06:50
6.3 Getting to Know Your Data 00:17:27
6.4 Data Quality Checks with peewee, Part 1 00:20:15
6.4 Data Quality Checks with peewee, Part 2 00:18:25
6.4 Data Quality Checks with peewee, Part 3 00:12:13
6.5 Dealing with Missing Data 00:10:44
6.6 EDA for Insight: Describing Data, Part 1 00:04:39
6.6 EDA for Insight: Describing Data, Part 2 00:18:05
6.6 EDA for Insight: Describing Data, Part 3 00:14:24
6.6 EDA for Insight: Describing Data, Part 4 00:20:17
6.7 Querying Across Datasets with Joins 00:08:25
6.8 Joins with peewee, Part 1 00:27:42
6.8 Joins with peewee, Part 2 00:26:49
6.9 Translating peewee to SQL 00:06:58
6.10 A Visual Introduction to Joins with SQL 00:14:49


Summary
Data Science Fundamentals Part 1: Summary 00:03:21