Python for Data Science Certification Training Course

Course preview

Data Science with Python

Lesson 00 - Course Overview 04:34

0.1 Course Overview 04:34

Lesson 01 - Data Science Overview 20:27

1.1 Introduction to Data Science 08:42

1.2 Different Sectors Using Data Science 05:59

1.3 Purpose and Components of Python 05:02

1.4 Quiz

1.5 Key Takeaways 00:44

Lesson 02 - Data Analytics Overview 18:20

2.1 Data Analytics Process 07:21

2.2 Knowledge Check

2.3 Exploratory Data Analysis(EDA)

2.4 EDA-Quantitative Technique

2.5 EDA - Graphical Technique 00:57

2.6 Data Analytics Conclusion or Predictions 04:30

2.7 Data Analytics Communication 02:06

2.8 Data Types for Plotting

2.9 Data Types and Plotting 02:29

2.10 Knowledge Check

2.11 Quiz

2.12 Key Takeaways 00:57

Lesson 03 - Statistical Analysis and Business Applications 23:53

3.1 Introduction to Statistics 01:31

3.2 Statistical and Non-statistical Analysis

3.3 Major Categories of Statistics 01:34

3.4 Statistical Analysis Considerations

3.5 Population and Sample 02:15

3.6 Statistical Analysis Process

3.7 Data Distribution 01:48

3.8 Dispersion

3.9 Knowledge Check

3.10 Histogram 03:59

3.11 Knowledge Check

3.12 Testing 08:18

3.13 Knowledge Check

3.14 Correlation and Inferential Statistics 02:57

3.15 Quiz

3.16 Key Takeaways 01:31

Lesson 04 - Python Environment Setup and Essentials 23:58

4.1 Anaconda 02:54

4.2 Installation of Anaconda Python Distribution (contd.)

4.3 Data Types with Python 13:28

4.4 Basic Operators and Functions 06:26

4.5 Quiz

4.6 Key Takeaways 01:10

Lesson 05 - Mathematical Computing with Python (NumPy) 30:31

5.1 Introduction to Numpy 05:30

5.2 Activity-Sequence it Right

5.3 Demo 01-Creating and Printing an ndarray 04:50

5.4 Knowledge Check

5.5 Class and Attributes of ndarray

5.6 Basic Operations 07:04

5.7 Activity-Slice It

5.8 Copy and Views

5.9 Mathematical Functions of Numpy 05:01

5.10 Assignment 01

5.11 Assignment 01 Demo 03:55

5.12 Assignment 02

5.13 Assignment 02 Demo 03:16

5.14 Quiz

5.15 Key Takeaways 00:55

Lesson 06 - Scientific computing with Python (Scipy) 23:35

6.1 Introduction to SciPy 06:57

6.2 SciPy Sub Package - Integration and Optimization 05:51

6.3 Knowledge Check

6.4 SciPy sub package

6.5 Demo - Calculate Eigenvalues and Eigenvector 01:36

6.6 Knowledge Check

6.7 SciPy Sub Package - Statistics, Weave and IO 05:46

6.8 Assignment 01

6.9 Assignment 01 Demo 01:20

6.10 Assignment 02

6.11 Assignment 02 Demo 00:55

6.12 Quiz

6.13 Key Takeaways 01:10

Lesson 07 - Data Manipulation with Pandas 47:34

7.1 Introduction to Pandas 12:29

7.2 Knowledge Check

7.3 Understanding DataFrame 05:31

7.4 View and Select Data Demo 05:34

7.5 Missing Values 03:16

7.6 Data Operations 09:56

7.7 Knowledge Check

7.8 File Read and Write Support 00:31

7.9 Knowledge Check-Sequence it Right

7.10 Pandas Sql Operation 02:00

7.11 Assignment 01

7.12 Assignment 01 Demo 04:09

7.13 Assignment 02

7.14 Assignment 02 Demo 02:34

7.15 Quiz

7.16 Key Takeaways 01:34

Lesson 08 - Machine Learning with Scikit–Learn 1:02:10

8.1 Machine Learning Approach 03:57

8.2 Steps 1 and 2 01:00

8.3 Steps 3 and 4

8.4 How it Works 01:24

8.5 Steps 5 and 6 01:54

8.6 Supervised Learning Model Considerations 00:30

8.7 Knowledge Check

8.8 Scikit-Learn 02:10

8.9 Knowledge Check

8.10 Supervised Learning Models - Linear Regression 11:19

8.11 Supervised Learning Models - Logistic Regression 08:43

8.12 Unsupervised Learning Models 10:40

8.13 Pipeline 02:37

8.14 Model Persistence and Evaluation 05:45

8.15 Knowledge Check

8.16 Assignment 01

8.17 Assignment 01 05:45

8.18 Assignment 02

8.19 Assignment 02 05:14

8.20 Quiz

8.21 Key Takeaways 01:12

Lesson 09 - Natural Language Processing with Scikit Learn 49:03

9.1 NLP Overview 10:42

9.2 NLP Applications

9.3 Knowledge check

9.4 NLP Libraries-Scikit 12:29

9.5 Extraction Considerations

9.6 Scikit Learn-Model Training and Grid Search 10:17

9.7 Assignment 01

9.8 Demo Assignment 01 06:32

9.9 Assignment 02

9.10 Demo Assignment 02 08:00

9.11 Quiz

9.12 Key Takeaway 01:03

Lesson 10 - Data Visualization in Python using matplotlib 32:46

10.1 Introduction to Data Visualization 08:02

10.2 Knowledge Check

10.3 Line Properties

10.4 (x,y) Plot and Subplots 10:01

10.5 Knowledge Check

10.6 Types of Plots 09:34

10.7 Assignment 01

10.8 Assignment 01 Demo 02:23

10.9 Assignment 02

10.10 Assignment 02 Demo 01:47

10.11 Quiz

10.12 Key Takeaways 00:59

Lesson 11 - Web Scraping with BeautifulSoup 52:27

11.1 Web Scraping and Parsing 12:50

11.2 Knowledge Check

11.3 Understanding and Searching the Tree 12:56

11.4 Navigating options

11.5 Demo3 Navigating a Tree 04:22

11.6 Knowledge Check

11.7 Modifying the Tree 05:38

11.8 Parsing and Printing the Document 09:05

11.9 Assignment 01

11.10 Assignment 01 Demo 01:55

11.11 Assignment 02

11.12 Assignment 02 demo 04:57

11.13 Quiz

11.14 Key takeaways 00:44

Lesson 12 - Python integration with Hadoop MapReduce and Spark 40:39

12.1 Why Big Data Solutions are Provided for Python 04:55

12.2 Hadoop Core Components

12.3 Python Integration with HDFS using Hadoop Streaming 07:20

12.4 Demo 01 - Using Hadoop Streaming for Calculating Word Count 08:52

12.5 Knowledge Check

12.6 Python Integration with Spark using PySpark 07:43

12.7 Demo 02 - Using PySpark to Determine Word Count 04:12

12.8 Knowledge Check

12.9 Assignment 01

12.10 Assignment 01 Demo 02:47

12.11 Assignment 02

12.12 Assignment 02 Demo 03:30

12.13 Quiz

12.14 Key takeaways 01:20

Project 1 18:36

Project 1 Stock Market Data Analysis

Project 1 Demo 18:36

Project 2 20:06

Project 02

Main project 02 20:06

Course Feedback

Course Feedback

Free Course Python Basics

Lesson 00 - Course Overview 04:44

0.1 Introduction 00:13

0.2 Offerings 00:07

0.3 Course Objectives 00:29

0.4 Course Overview 00:21

0.5 Target Audience 00:27

0.6 Course Prerequisites 00:11

0.7 Need of Python 00:49

0.8 Python vs. Rest Other Languages 00:25

0.9 Value to the Professionals 00:16

0.10 Value to the Professionals (contd.) 00:31

0.11 Value to the Professionals (contd.) 00:24

0.12 Lessons Covered 00:23

0.13 Conclusion 00:08

Lesson 01 - Introduction to Python 28:15

1.1 Introduction 00:12

1.2 Objectives 00:16

1.3 An Introduction to Python 01:27

1.4 Features of Python 00:44

1.5 The History of Python 00:27

1.6 Releases 00:33

1.7 Installation on Ubuntu-based Machines 01:00

1.8 Installation on Windows 00:59

1.9 Demo-Install and Run Python 00:08

1.10 Demo-Install and Run Python 14:17

1.11 Example of a Python Program 01:08

1.12 Modes of Python 00:27

1.13 Batch Script Mode 00:29

1.14 Demo-Run Python in the Batch Mode 00:05

1.15 Demo-Run Python in the Batch Mode 01:14

1.16 Interpreter Mode 00:46

1.17 Demo-Run Python in the Interpreter Mode 00:05

1.18 Demo-Run Python in the Interpreter Mode 00:31

1.19 Indentation in Python 00:49

1.20 Indentation in Python (contd.) 00:26

1.21 Writing Comments in Python 01:06

1.22 Business Scenario 00:23

1.23 Quiz

1.24 Summary 00:33

1.25 Conclusion 00:10

Lesson 02 - Python Data Types 19:34

2.1 Python Data Types 00:10

2.2 Objectives 00:18

2.3 Variables 00:52

2.4 Types of Variables 01:09

2.5 Types of Variables-String 01:07

2.6 Types of Variables-Numeric Types 00:34

2.7 Types of Variables-Boolean Variables 00:34

2.8 Types of Variables-Boolean Variables (contd.) 00:35

2.9 Types of Variables-List 00:24

2.10 Adding Elements to a List 00:48

2.11 Accessing the Elements of a List 01:09

2.12 Types of Variables-Dictionary 00:30

2.13 Adding Elements to a Dictionary 00:50

2.14 Accessing the Elements of a Dictionary 00:12

2.15 Dictionary Methods 00:32

2.16 Dictionary Methods (contd.) 00:30

2.17 Operators 00:21

2.18 Opeators (contd.) 00:10

2.19 Logical Operators 00:44

2.20 Logical Operators (contd.) 00:47

2.21 Logical Operators (contd.) 00:39

2.22 Arithmetic Operations on Numeric Values 00:58

2.23 Order of Operands 01:03

2.24 Operators on Strings 01:03

2.25 Variables Comparison 01:06

2.26 Variables Comparison (contd.) 01:05

2.27 Variables Comparison (contd.) 00:33

2.28 Quiz

2.29 Summary 00:41

2.30 Conclusion 00:10

Lesson 03 - Control Statements 09:27

3.1 Introduction 00:10

3.2 Objectives 00:13

3.3 Pass Statements 00:15

3.4 Conditional Statements 00:45

3.5 Types of Conditional Statements 00:18

3.6 If Statements 00:28

3.7 If…Else Statements 00:49

3.8 If…Else If Statements 01:06

3.9 If…Else If…Else Statements 00:18

3.10 Nested If Statements 00:38

3.11 Demo-Use “If…Else” Statement 00:05

3.12 Demo-Use “If…Else” Statement 02:12

3.13 In Clause 00:56

3.14 Ternary Operators 00:44

3.15 Quiz

3.16 Summary 00:21

3.17 Conclusion 00:09

Lesson 04 - Loops 08:10

4.1 Introduction 00:10

4.2 Objectives 00:12

4.3 Loops in Python 00:37

4.4 Range Function 00:28

4.5 For Loop 00:35

4.6 For Loop (contd.) 00:23

4.7 While Loop 00:35

4.8 Nested Loop 00:50

4.9 Demo-Create Loops 00:05

4.10 Demo-Create Loops 02:21

4.11 Break Statements 00:48

4.12 Continue Statements 00:36

4.13 Quiz

4.14 Summary 00:22

4.15 Conclusion 00:08

Lesson 05 - Functions 09:27

5.1 Introduction 00:10

5.2 Objectives 00:13

5.3 Introduction to Functions 00:49

5.4 Creating Functions 00:49

5.5 Calling Functions 00:43

5.6 Arguments and Return Statement 01:28

5.7 Variable-Length Arguments 00:53

5.8 Variable-Length Arguments (contd.) 00:33

5.9 Recursion 00:43

5.10 Demo-Create a Function 00:05

5.11 Demo-Create a Function 02:19

5.12 Quiz

5.13 Summary 00:33

5.14 Conclusion 00:09

Lesson 06 - Classes 11:23

6.1 Introduction 00:10

6.2 Objectives 00:14

6.3 Classes 01:39

6.4 Objects 00:33

6.5 Creating a Basic Class 00:35

6.6 Accessing Variables of a Class 00:39

6.7 Adding Functions to a Class 00:40

6.8 Built-in Class Attributes 00:37

6.9 Init Function 00:38

6.10 Example of Defining and Using a Class 00:42

6.11 Example of Defining and Using a Class (contd.) 00:27

6.12 Demo-Create a Class 00:05

6.13 Demo-Create a Class 03:34

6.14 Quiz

6.15 Summary 00:40

6.16 Conclusion 00:10

Lesson 07 - Imports and Modules 12:01

7.1 Introduction 00:11

7.2 Objectives 00:16

7.3 Modules 00:54

7.4 Creating Modules 00:18

7.5 Using Modules 00:14

7.6 Using Modules (contd.) 01:10

7.7 Using Modules (contd.) 00:27

7.8 Using Modules (contd.) 00:26

7.9 Python Interpreter Module Search 00:57

7.10 Demo-Create and Import a Module 00:06

7.11 Demo-Create and Import a Module 02:24

7.12 Namespace and Scoping 00:57

7.13 Dir() Function 00:29

7.14 Dir() Function (contd.) 00:23

7.15 Global and Local Functions 00:31

7.16 Reload a Module 00:48

7.17 Packages in Python 00:46

7.18 Quiz

7.19 Summary 00:34

7.20 Conclusion 00:10