Data Analysis with Python

Focused View

Prashant Mishra

19:31:09

0 View

1. Introduction to Business and Data

1.1 Supported Files-PPTs.zip

1. Introduction to Bussiness and Data.mp4

17:26

2. Python Basics and Jupyter Notebooks

1. Python Basics and Jupyter Notebook.mp4

14:09

2. Python Basics and Jupyter Notebook- Lab Session.mp4

25:01

3. Python Basics and Jupyter Notebook- Lab Session Continued.mp4

22:20

3. Basic Python Syntax

1. Basic Python Syntax.mp4

25:54

2. Basic Python Syntax Practical.mp4

27:14

3. Basic Python Syntax Practical Continued.mp4

16:50

4. Basic Python Syntax Practical Continued.mp4

34:51

5. Basic Python Syntax Practical Continued.mp4

26:16

6. Conditional Programming in Python.mp4

16:21

7. Conditional Programming in Python Practical.mp4

30:38

8. Conditional Programming in Python Practical Continued.mp4

23:27

9. Conditional Programming in Python Practical Continued.mp4

34:33

4. Functions and Sequences

1. Functions and Sequences.mp4

19:55

2. Functions and Sequences Practicle session.mp4

21:03

3. Functions and Sequences Practicle session Continued.mp4

26:09

4. Functions and Sequences Practicle session Continued.mp4

26:24

5. Functions and Sequences Practicle session Continued.mp4

28:38

6. Functions and Sequences Practicle session Continued.mp4

24:45

5. Object-Oriented Programming (OOP) and NumPy

1. Object Oriented Programming (OOPS) and Numpy.mp4

18:46

2. Object Oriented Programming (OOPS) and Numpy Practical session.mp4

27:41

3. Object Oriented Programming (OOPS) and Numpy Practical session Continued.mp4

17:10

4. Object Oriented Programming (OOPS) and Numpy Practical session continued.mp4

29:45

5. Object Oriented Programming (OOPS) and Numpy Practical session continued.mp4

31:04

6. Object Oriented Programming (OOPS) and Numpy Practical session continued.mp4

14:59

6. Pandas Library and Data Manipulation

1. Pandas Library and Data Manipulation.mp4

25:17

2. Pandas Library and Data Manipulation Part-2.mp4

28:03

3. Pandas Library and Data Manipulation Part-3.mp4

29:00

7. Working with Files and Data Importing

1. Working with Files and Data Importing.mp4

30:15

2. Working with Files and Data Importing (Part-2).mp4

30:36

3. Working with Files and Data Importing (Part-3).mp4

15:50

8. Data Cleaning and Preprocessing

1. Data Cleaning and Preprocessing.mp4

35:30

2. Data Cleaning and Preprocessing Part- 3.mp4

35:14

3. Pandas Methods and Operations.mp4

20:01

4. Pandas Methods and Operations Part-2.mp4

33:59

5. Pandas Methods and Operations Part-3.mp4

18:33

6. Assignment.mp4

17:50

7. Data Cleaning and Preprocessing Part-2.mp4

35:59

8. Assignment Solution.mp4

20:41

9. Exploratory Data Analysis (EDA)

1. Exploratory Data Analysis (EDA).mp4

33:02

2. Exploratory Data Analysis (EDA) Part-2.mp4

31:50

10. Advanced Topics

1. Data Gathering and API.mp4

27:04

2. Linear Algebra and Advance mathematics in Data Analytics.mp4

18:20

11. Capstone Project

1. Capstone Project.mp4

05:24

2. Project Solution Part-1.mp4

34:27

3. Project Solution Part-2.mp4

28:14

4. Project Solution Part-3.mp4

14:41

Description

Master data analysis using Python, pandas, NumPy, data visualization, and real-world projects.

What You'll Learn?

Students will learn to analyze business data using Python and essential libraries like pandas and NumPy.
Students will visualize data effectively with popular Python libraries such as Matplotlib and Seaborn.
Students will perform data cleaning, preprocessing, and exploratory data analysis (EDA).
Students will execute real-world data analysis projects, including data gathering and API utilization.

Who is this for?

Aspiring data analysts looking to start a career in data science and analytics.

Professionals seeking to enhance their data analysis skills with Python.

Students and beginners interested in learning data analysis and Python programming.

Anyone eager to understand and apply data analytics in real-world scenarios.

What You Need to Know?

Basic understanding of computer operations.

No prior programming experience needed; all necessary concepts will be taught.

A computer with internet access to install Python and related tools.

More details

Description
In this comprehensive course, "Data Analysis with Python," you will embark on a journey to become a proficient data analyst equipped with the essential skills and tools needed to analyze, visualize, and interpret data effectively. This course is designed for beginners and professionals alike, providing a solid foundation in data analysis using Python.

Throughout the course, you will:
Learn the fundamentals of Python programming and its application in data analysis.
Explore key libraries such as pandas and NumPy for data manipulation and analysis.
Gain expertise in data cleaning, preprocessing, and handling missing values.
Develop skills in exploratory data analysis (EDA) and create insightful visualizations using Matplotlib and Seaborn.
Understand the principles of file handling and data importing from various sources including CSV, JSON, and Excel.
Apply advanced techniques such as object-oriented programming (OOP) and work on real-world data analysis projects.
Learn to gather data from APIs, perform linear algebra operations with NumPy, and execute a comprehensive capstone project.

By the end of this course, you will have the confidence and skills to tackle complex data analysis tasks, making you a valuable asset in any data-driven organization.
Whether you are an aspiring data analyst, a professional looking to enhance your data skills, or a student interested in data science, this course will provide you with the knowledge and hands-on experience needed to excel in the field of data analysis.
Who this course is for:
Aspiring data analysts looking to start a career in data science and analytics.
Professionals seeking to enhance their data analysis skills with Python.
Students and beginners interested in learning data analysis and Python programming.
Anyone eager to understand and apply data analytics in real-world scenarios.

User Reviews

Rating

average 0

Total votes0

Focused display

Data Analysis

Prashant Mishra

Instructor's Courses

I am Computer Science Graduate in 2021 and with a passion for teaching, started back as a BDA in various Ed-tech companies, which increased a little more passion towards this industry to explore.Have trained more than 5000+ Individual students one-on-one and group-based, which not only found my classes very interesting but also developed a huge scope of job opportunities in the future.

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.