Python and Analytics for Data Science and Machine Learning

Focused View

Mohit Jain

8:22:49

142 View

1. Course Introduction and Structure

1. Introduction.mp4

08:05

2. Course Introduction.html

2. Introduction to Variables and Strings

1. Introduction to Variables.mp4

07:18

2. Variables, Datatypes and Expressions.mp4

12:55

3. Variables and Datatypes.html

4. Classroom 1 Hands-on Exercise on Variables and Expressions.mp4

05:48

5. Homework Hands-on Exercise on Variables and Expressions.html

6. Introduction to Strings and Functions.mp4

19:22

7. Strings and its Functions.html

8. Classroom 2 Hands-on Exercise on Strings.mp4

11:27

9. Homework Strings and its Functions.html

3. List, Tuple and Dictionary

1. Introduction to List.mp4

06:02

2. List and its Functions.mp4

21:23

3. List and its Functions.html

4. Introduction to Tuples and Dictionary.mp4

17:01

5. Tuples and Dictionary.html

6. Classroom 3 Hands-on Exercise on List and Tuples.mp4

09:01

7. Classroom 4 Hands-on Exercise on Dictionary.mp4

08:59

4. Conditions and Loops

1. If-Else Conditions and Logical Operators.mp4

12:51

2. Conditions and Logical Operators.html

3. Classroom 5 Hands-on Exercise on Conditions.mp4

09:39

4. Loops (For and While).mp4

13:43

5. List Comprehension.mp4

18:39

6. Loops and List Comprehension.html

7. Classroom 6 Hands-on Exercise on Loops.mp4

09:54

5. Functions and Case Study 1

1. Introduction to Functions and Return Statement.mp4

25:59

2. Introduction to Functions.html

3. Classroom 7 Hands-on Functions.mp4

10:23

4. Homework List, Tuples, Dictionary, Loops, Conditions, Functions.html

5. Case Study 1 Loan Risk Analysis.mp4

07:45

6. Data Science Numpy and Functions

1. Introduction to Numpy Package.mp4

09:01

2. Introduction to Numpy.html

3. Part 1 Numpy Functions.mp4

10:51

4. Part 1 Numpy Functions.html

5. Part 2 Numpy Functions.mp4

11:21

6. Part 2 Numpy Functions.html

7. Part 3 Numpy Functions.mp4

17:02

8. Part 3 Numpy Functions.html

9. Classroom 8 Hands-on Exercise on Numpy Package.mp4

08:28

7. Data Science Pandas Package and Case Study 2

1. Introduction to Pandas Series.mp4

09:27

2. Pandas Series.html

3. Introduction to Pandas DataFrame.mp4

13:49

4. Create Pandas DataFrame.html

5. Access Pandas DataFrame.mp4

08:50

6. Access Pandas DataFrame.html

7.1 storecities.csv

7.2 train.csv

7. Part 1 Pandas Functions.mp4

31:29

8.1 storecities.csv

8.2 train.csv

8. Part 2 Pandas Functions.mp4

37:10

9. Pandas Package.html

10.1 ities.xlsx

10.2 storecities.csv

10. Part 1 Classroom 9 Hands-on Exercise on Numpy and Pandas.mp4

11:09

11.1 ities.xlsx

11.2 storecities.csv

11. Part 2 Classroom 9 Hands-on Exercise on Numpy and Pandas.mp4

10:35

12.1 homework4.pdf

12.2 homework5_bigmart.xlsx

12.3 product_data.csv

12. Homewrok 4 Numpy and Pandas Libraries.html

13.1 churn_prediction_course.csv

13. Case Study 2 Churn Prediction.mp4

12:15

8. Data Science Data Visualization

1.1 product_data.csv

1.2 train.csv

1. Introduction to Visualization.mp4

05:47

2.1 product_data.csv

2.2 train.csv

2. Visualization Matplotlib and Seaborn Packages.mp4

40:21

3. Data Visualization.html

4. Part 1 Classroom 10 Hands-on Exercise on Visualization.mp4

12:02

5. Part 2 Classroom 10 Hands-on Exercise on Visualization.mp4

06:05

6.1 homework5_bigmart.xlsx

6.2 homework5.pdf

6.3 product_data.csv

6. Homework 5 Data Visualization.html

9. Case Study 3 and Projects

1.1 clustering_course.csv

1. Case Study 3 Customer Segmentation.mp4

10:53

2.1 nyc_taxi_trip_duration.xlsx

2. Project 1 New York Trip Duration.html

3.1 titanic_dataset.csv

3. Project 2 Titanic Disaster.html

Description

Kick Start Your Data Science Career from Beginner to Master

What You'll Learn?

Become Expert at Python fundamentals and Data Science Packages such as Pandas, Numpy and Visualization
This Course is ideal for anyone to start their Data Science Journey
Practice and Hands-on concepts through Quizzes, Classroom, Homework Assignments, Case Studies and Projects
Opportunity to Apply Data Science Concepts into 3 Real World Case Studies and 2 Real World Projects
This course covers all the important Python Fundamentals and Data Science Concepts requires to succeed in Academics and Corporate Industry

Who is this for?

This course is meant for anyone who wants to get expert on Python programming concepts and Data Science libraries for analysis, machine Learning models etc.

They can be students, professionals, Data Scientist, Business Analyst, Data Engineer, Machine Learning Engineer, Project Manager, Leads, business reports etc.

What You Need to Know?

There is no technical or prior programming knowledge is required. This course only requires your commitment and practice to become expert at Python.

It requires your local desktop/Laptop (Windows or Mac) or Google Account (Optional)

More details

Description
This course is meant for beginners and intermediates who wants to expert on Python programming concepts and Data Science libraries for analysis, machine Learning models etc.
They can be students, professionals, Data Scientist, Business Analyst, Data Engineer, Machine Learning Engineer, Project Manager, Leads, business reports etc.
The course have been divided into 6 parts - Chapters, Quizzes, Classroom Hands-on Exercises, Homework Hands-on Exercises, Case Studies and Projects.
Practice and Hands-on concepts through Classroom, Homework Assignments, Case Studies and Projects
This Course is ideal for anyone who is starting their Data Science Journey and building ML models and Analytics in future.
This course covers all the important Python Fundamentals and Data Science Concepts requires to succeed in Academics and Corporate Industry.
Opportunity to Apply Data Science Concepts in 3 Real World Case Studies and 2 Real World Projects.
The 3 Case Studies are on Loan Risk Analysis, Churn Prediction and Customer Segmentation.
The 2 Projects are on Titanic Dataset and NYC Taxi Trip Duration.
The recommended approach for this course - Follow the chapters in their order, Do Yourself all the Hands-on Exercises. Finally, Consistency, discipline and practice is paramount.
This course will not teach you how to build and develop ML models. But, make you expert at python programming language which is needed to build ML models.
Who this course is for:
This course is meant for anyone who wants to get expert on Python programming concepts and Data Science libraries for analysis, machine Learning models etc.
They can be students, professionals, Data Scientist, Business Analyst, Data Engineer, Machine Learning Engineer, Project Manager, Leads, business reports etc.

User Reviews

Rating

average 0

Total votes0

Focused display

I am passionate data enthusiast and loved to mentor people. My ultimate goal is to bring value in people life.I have 10+ years of professional experience and worked 7 years at American Express at different levels of leadership.Currently, I am working at Fintech company and leading the Credit Risk team and objective is to build model to predict the credit worthiness of customer and help the company to find quality customer that in turn generate profits and minimized the loses and write-offs.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.