Advanced Data Analytics Course: Become a Data Analyst 2024

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Datagai Academy / Ganeshraj Shetty

23:38:12

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1. Introduction to Python and its Environment

1. 1. Motivation for learning Python.mp4

05:56

2. 2. Python Introduction.mp4

08:58

3. 3. Introduction to Anaconda and Jupyter Note Book.mp4

07:01

4. 4. Anaconda Installation.mp4

09:26

5. 5. Introduction to Jupyter Notebook Interface.mp4

08:54

2. 2. Introduction to Python Programming

1. 1 Syntax of a Programming language.mp4

10:17

2. 2 Newline Character.mp4

02:28

3. 3 Elements Keywords Identifiers.mp4

11:03

4. 4.Comments Statement.mp4

08:19

5. 5 Variable Assignment.mp4

13:46

6. 6 Data Type I in Python Programming.mp4

09:02

7. 7. Data Type II.mp4

31:48

8. 8 Type Conversion of Data Type.mp4

08:20

9. 9 Output Formatting and Input Function.mp4

13:36

10. 10 Operators in Python Programming.mp4

25:35

11. 11 IF Statements.mp4

19:56

12. 12 While loop Statements.mp4

14:35

13. 13 For loop Statement.mp4

41:33

14. 14 Break and Continue Statement.mp4

17:52

15. 15 Lists-I.mp4

20:38

16. 16 Lists-II.mp4

25:22

17. 17 Tuples.mp4

19:48

18. 18 Strings.mp4

25:16

19. 19 Sets.mp4

29:52

20. 20 Dictionary.mp4

21:52

21. 21 Functions.mp4

27:23

22. 22 Function Arguments and parameters.mp4

14:35

23. 23 Built-in Functions.mp4

16:53

24. 24 Recursive Function.mp4

09:48

25. 25 Lambda Function.mp4

09:29

26. 26 Modules, Package and Libraries.mp4

19:04

27. 27 File IO Operation.mp4

26:20

28. 28 Working with Python directory and files.mp4

10:02

29. 29 Exception handling with python.mp4

15:58

30. 30 Comprehension in Python.mp4

10:39

31. Project 1- Twitter Data Analysis.mp4

17:42

32. Project 2- Twitter Data Analysis.mp4

11:18

33. Project 3- Twitter Data Analysis.mp4

06:02

34. Project 4- Twitter Data Analysis.mp4

08:41

35. Project 5- Twitter Data Analysis.mp4

04:01

3. Data Visualization using Matplotlib

1. 1. Introduction to Matplotlib.mp4

02:00

2. 2. Line Chart Plot.mp4

14:55

3. 3. Plotting a Bar Chart.mp4

12:44

4. 4. Histogram and Scatter Plot.mp4

06:07

5. 5. Stack Plot and Pie Plot.mp4

08:43

6. 6. Subplots.mp4

11:48

4. Numpy for Data Science

1. 1. Numpy Introduction.mp4

15:49

2. 2. Numpy Array Creation.mp4

15:51

3. 3. Numpy Arange Reshape.mp4

10:45

4. 4. Numpy Array Conversion.mp4

13:28

5. 5. Accessing Array Values.mp4

22:44

6. 6. Numpy Operations.mp4

23:00

7. 7. Fancy Indexing and Sorting Arrays.mp4

15:38

8. 8. Array Products and Concatenation.mp4

23:11

9. 9. Broadcasting.mp4

14:50

5. Pandas for Data Science

1. 1. Pandas Introduction.mp4

04:34

2. 2. Pandas Series.mp4

21:23

3. 3. Pandas DataFrames.mp4

24:43

4. 4. Handling missing data.mp4

25:56

5. 5. Conditional Selection and Reindexing.mp4

11:56

6. 6. Data Input and Data Output.mp4

11:38

7. 7. Data Processing.mp4

22:37

8. 8. Grouping and Pivot table.mp4

15:59

9. 9. Concatenating Dataframes and Inserting Rows.mp4

13:56

10. 10. Concatenation and Merging Logic.mp4

19:09

11. 11. Merging and Joining.mp4

15:44

12. 12. Cartesian Product Between DataFrames.mp4

05:55

13. 13. Handling Duplicates in a DataFrames.mp4

12:31

14. 14. String Handling.mp4

23:03

6. Handling Dates using Pandas

1. 1. DateTime - Datetime Creation.mp4

11:38

2. 2. DateTime - Pandas datetime functions.mp4

11:40

3. 3. DateTime - Reading Dates with Informats.mp4

25:44

4. 4. DateTime Series- DateRange and DateOffs.mp4

13:43

7. Probability and Statistics for Data Science

1. 1. Introduction to Statistics.mp4

06:33

2. 2. Introduction to inferential Statistics.mp4

08:48

3. 3. Measures of Central Tendencies.mp4

13:11

4. 4. Measures of Dispersion.mp4

10:40

5. 5. Introduction to Probability.mp4

09:43

6. 6. Types of Probability functions.mp4

05:46

7. 7. Probability density function.mp4

17:32

8. 8. Cumulative Distribution function.mp4

16:07

9. 9. Skewness and Kurtosis.mp4

09:17

10. 10. Boxplot.mp4

17:43

11. 11. KDE plot.mp4

17:43

12. 12. Covariance.mp4

15:20

13. 13. Correlation and Causation.mp4

21:32

14. 14. Introduction to Linear regression.mp4

18:51

8. Exploratory Data Analysis for Data Science

1. 1. Exploratory Data Analysis using Classroom DataSet.mp4

21:42

2. 2. Exploratory Data Analysis using IMD Rainfall DataSet.mp4

30:56

3. 3. Exploratory Data Analysis of Real Estate Dataset.mp4

25:45

4. 4. Exploratory Data Analysis using IPL player performance Dataset.mp4

28:33

Description

Comprehensive Data Science Skills for Machine Learning, Deep Learning, Artificial Intelligence using Python Programming

What You'll Learn?

All the skills required to become a Data Analyst, Business Analyst, Sports Analyst or similar roles.
All Python modules required to become a Robust Machine Learning Engineer.
Complete Data Analytical Skills, Advanced Data Visualization Skills, Data Automation Skills, Data Manipulation Skills using Python Programming with Examples.
Complete foundations Skills required to make a smooth transition into Data Science and Machine Learning.
To grow from Zero to a Successful Analyst in any domain.

Who is this for?

For Students who wish to work as a Data Analyst or Similar Roles.

For Candidate who wish to make a transition into Data Science.

For Candidates who wish to add Python for Data Science as a Skill.

For Programmers who wish to transition into Data Science.

For Candidates who wish to unravel the potential of Automation using Python.

What You Need to Know?

There are no prerequisites for taking up this course.

Students from any background without programming knowledge or experience can take this course.

You need to have an Analytical thinking & liking for Math and Numbers.

More details

Description
The "Advanced Data Analytics Course" is a comprehensive hands-on program meticulously designed to equip participants with the fundamental skills and knowledge required to excel as a Data Analyst in the dynamic fields of Data Analysis and Data Analytics. Throughout the course, students delve into key concepts, techniques, and tools essential for leveraging data to extract meaningful insights and perform advanced Data Analysis using attractive visualization techniques.
The course begins with an introduction to the foundations of Python for Data Analytics, covering topics such as data manipulation, cleaning, and visualization using popular Python libraries such as NumPy, Pandas, Matplotlib, Plotly, Seaborn, ,Scipy etc. Special emphasis is placed on the practical application of each concept using real-life examples to analyze datasets, identify patterns, and develop strong Data Analyst skills.
By the end of the program, students will have developed a robust foundation in Data Analytics for machine learning, enabling them to confidently tackle complex Data Analysis challenges, make data-driven decisions, and contribute effectively as Data Analysts across various domains. Whether you are an aspiring Data Analyst or a professional looking to upskill, this course equips you with the necessary tools and expertise to thrive in today's data-driven world.
The course has been curated meticulously, ensuring that every topic is delivered effectively to maximize your learning experience. Join the "Advanced Data Analytics Course" and unlock your potential as a Data Analyst, mastering the art of Data Analysis and Data Analytics.
Who this course is for:
For Students who wish to work as a Data Analyst or Similar Roles.
For Candidate who wish to make a transition into Data Science.
For Candidates who wish to add Python for Data Science as a Skill.
For Programmers who wish to transition into Data Science.
For Candidates who wish to unravel the potential of Automation using Python.

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Data Analysis

Datagai Academy / Ganeshraj Shetty

Instructor's Courses

Welcome to the world of data mastery at Udemy! I'm thrilled to guide you through your journey in unlocking the power of data analytics and machine learning. With a passion for problem-solving and a commitment to continuous learning, I bring a unique blend of expertise in Excel, SAS programming, Python, and machine learning algorithms to the table.My journey into the realm of data analytics began with a deep dive into Excel. Starting from the basics, I meticulously honed my skills, gradually transitioning into an expert in Advanced Excel techniques. This foundation provided me with a solid understanding of data manipulation and analysis, setting the stage for my subsequent ventures.Driven by a thirst for knowledge and a desire to expand my toolkit, I embarked on the challenging path of mastering SAS programming. Achieving both Base and Advanced SAS Programmer credentials, I conquered what is widely regarded as one of the toughest examinations in the field of data analytics. I gained global credentials in SAS programming without any training, which gave me a strong belief in my learning capabilities, which I have leveraged in each of my courses.But my quest for mastery didn't stop there. Recognizing the growing importance of Python in the data science landscape, I eagerly embraced this versatile programming language. Delving deep into Python's capabilities, I immersed myself in machine learning algorithms, mastering techniques that empower us to extract insights and make informed decisions from vast troves of data.Fueled by my passion for empowering others with knowledge, I ventured into course creation, distilling my expertise into comprehensive learning resources. Whether you're just starting out or looking to elevate your skills to the next level, my courses are crafted to provide you with the guidance and practical skills you need to succeed in the dynamic field of data analytics and machine learning.Throughout my journey in the realm of Data Science and Machine Learning, I've come to understand the immense breadth of knowledge awaiting students. Recognizing the value of efficient learning, I've meticulously designed my courses to optimize learning time. By curating content thoughtfully, I ensure that students can absorb more in less time, empowering them to accelerate their learning journey effectively.I have adorned the roles of being a Data Analyst, SAS Analyst, SAS Programmer, Machine Learning Engineer and as a Researcher before creating these courses for the benefit of the Data Science community. Join me on this exhilarating journey as we unravel the mysteries of data together and unleash its transformative potential.

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