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1.1 Financial+Sample.xlsx |
81.46KB |
1. Connect to data source.mp4 |
17.25MB |
1. Create a virtual environment on Windows.mp4 |
16.26MB |
1. Introduction.mp4 |
1.48MB |
1. Introduction to Excel.mp4 |
13.39MB |
1. Introduction to SQL.mp4 |
17.37MB |
1. What is Power BI.mp4 |
37.02MB |
1. What is Power Query.mp4 |
13.62MB |
1. What is Python.mp4 |
16.73MB |
10.1 AddData.xlsx |
14.79MB |
10. Adding a title to worksheet.mp4 |
17.61MB |
10. Importing data and creating relationships.mp4 |
40.57MB |
10. Joining Multiple Tables with INNER Join.mp4 |
58.65MB |
10. The Notebook user interface.mp4 |
16.42MB |
10. The Sakilla Database.mp4 |
6.39MB |
11.1 Lookups.xlsx |
14.85MB |
11. Creating a new notebook.mp4 |
20.02MB |
11. Creating lookups with DAX.mp4 |
39.89MB |
11. Establishing a connection to the database.mp4 |
21.10MB |
11. Joining Multiple Tables with LEFT Join.mp4 |
29.46MB |
11. Saving your work.mp4 |
24.38MB |
12. Analyze data with Pivot Tables.mp4 |
49.68MB |
12. Introduction to Excel Functions and Formulas.mp4 |
23.85MB |
12. Joining Multiple Tables with RIGHT Join.mp4 |
20.51MB |
12. Python expressions.mp4 |
10.20MB |
12. Write a Python function to execute SQL queries.mp4 |
11.04MB |
13.1 Charts.xlsx |
17.28MB |
13. Analyze data with Pivot Charts.mp4 |
52.40MB |
13. Asking relevant questions about the data.html |
1.08KB |
13. Joining Multiple Tables with SELF Join.mp4 |
39.55MB |
13. Python statements.mp4 |
14.55MB |
13. Using formulas for arithmetic tasks.mp4 |
28.14MB |
14.1 Refresh.xlsx |
17.28MB |
14. Python Comments.mp4 |
12.96MB |
14. Refreshing source data.mp4 |
49.10MB |
14. Removing duplicates from query results.mp4 |
27.73MB |
14. Re-using formulas.mp4 |
20.24MB |
14. What are the most popular film categories rented by customers.mp4 |
77.69MB |
15.1 Update.xlsx |
17.31MB |
15. Calculating YTD Profits.mp4 |
35.18MB |
15. Group data by combing rows.mp4 |
19.37MB |
15. How does the average rental duration vary across film categories.mp4 |
42.62MB |
15. Python data types.mp4 |
14.95MB |
15. Updating queries.mp4 |
66.45MB |
16. Calculating percentage change.mp4 |
27.80MB |
16. Casting data types.mp4 |
7.80MB |
16. Creating new reports.mp4 |
43.59MB |
16. Filter grouped results.mp4 |
38.85MB |
16. Which actors are featured in the most rented films.html |
3.00KB |
17. Are there any seasonal trends in the rental volume.html |
4.26KB |
17. Python Variables.mp4 |
24.51MB |
17. Relative and absolute reference.mp4 |
42.24MB |
17. Sort query results.mp4 |
42.14MB |
18. Filtering rows of data.mp4 |
12.22MB |
18. Python List.mp4 |
35.55MB |
18. Using Rank Function.mp4 |
18.70MB |
18. What is the average rental cost by film category.html |
2.80KB |
19. How does the revenue contribution from different film categories compare.html |
3.11KB |
19. Introduction to aggregate functions.mp4 |
6.21MB |
19. Python Tuple.mp4 |
24.20MB |
19. STD Function.mp4 |
11.10MB |
2. Connecting to a data source.mp4 |
31.11MB |
2. Course Introduction.html |
1.90KB |
2. Create a virtual environment on Macs.mp4 |
22.27MB |
2. Installing Python on Windows.mp4 |
22.79MB |
2. Introduction to MySQL.mp4 |
16.44MB |
2. Opening a new workbook.mp4 |
29.77MB |
2. Transform the data.mp4 |
26.58MB |
2. What is Power BI Desktop.mp4 |
11.78MB |
20. Are there any correlations between film length and rental frequency.html |
2.83KB |
20. Python dictionaries.mp4 |
41.40MB |
20. Small and Large Functions.mp4 |
17.54MB |
20. Using COUNT Aggregate Function.mp4 |
44.58MB |
21. Download the Python files.html |
45B |
21. Median Function.mp4 |
9.10MB |
21. Python Operators.mp4 |
54.56MB |
21. Using SUM Aggregate Function.mp4 |
20.10MB |
22. Count and Counta Functions.mp4 |
17.36MB |
22. Python Conditional statements.mp4 |
24.77MB |
22. Using AVG Aggregate Function.mp4 |
15.41MB |
23. Exploring fonts.mp4 |
24.85MB |
23. Python Loops.mp4 |
30.28MB |
23. Using MIN Aggregate Function.mp4 |
10.45MB |
24. Adjusting column width and row height.mp4 |
34.48MB |
24. Python Functions.mp4 |
22.10MB |
24. Using MAX Aggregate Function.mp4 |
12.15MB |
25. Using alignment.mp4 |
29.48MB |
25. What are Subqueries.mp4 |
21.12MB |
26. Designing borders.mp4 |
26.34MB |
26. Using Nested Subqueries.mp4 |
15.29MB |
27. Formatting Numbers.mp4 |
38.22MB |
28. Conditional formatting.mp4 |
43.27MB |
29. Creating tables.mp4 |
42.83MB |
3. Activate a virtual environment on Windows.mp4 |
4.29MB |
3. Data Analysis Overview.mp4 |
30.66MB |
3. Entering data in Excel.mp4 |
31.72MB |
3. Installing Python on Macs.mp4 |
28.86MB |
3. Install Power BI Desktop.mp4 |
14.15MB |
3. Model the data.mp4 |
17.63MB |
3. MySQL Installation (Windows).mp4 |
69.63MB |
3. Please Read.html |
189B |
30. Inserting shapes.mp4 |
37.79MB |
4.1 Prep.xlsx |
14.79MB |
4. Activate a virtual environment on Macs.mp4 |
12.08MB |
4. Basic data entry in Excel.mp4 |
28.13MB |
4. Explore Power BI Desktop Interface.mp4 |
24.77MB |
4. MySQL Installation (Mac).mp4 |
41.35MB |
4. Preparing the query.mp4 |
45.33MB |
4. Roles in Data Analysis.mp4 |
39.24MB |
4. Visualize the data.mp4 |
58.70MB |
4. What is Jupyter Notebook.mp4 |
4.48MB |
5.1 Cleansing.xlsx |
14.78MB |
5. Cleaning the data.mp4 |
73.42MB |
5. Entering data with autofil.mp4 |
27.40MB |
5. Installing Jupyter Notebook.mp4 |
30.28MB |
5. Microsoft 365 Setup.mp4 |
23.24MB |
5. Publish report to Power BI Service.mp4 |
11.65MB |
5. Tasks of a Data Analyst.mp4 |
50.96MB |
5. Upgrade Pip.mp4 |
6.43MB |
5. What is MySQL Workbench.mp4 |
33.75MB |
6.1 Enhance.xlsx |
13.37MB |
6. Basic database concepts.mp4 |
34.76MB |
6. Build a dashboard.mp4 |
43.83MB |
6. Enhancing the query.mp4 |
79.24MB |
6. Entering date.mp4 |
24.18MB |
6. Getting started with Microsoft 365.mp4 |
22.10MB |
6. Importance of Data-Driven Decision Making.html |
3.24KB |
6. Install Visual Studio Code.mp4 |
31.32MB |
6. Running Jupyter Notebook Server.mp4 |
42.03MB |
7. Collaborate and share.mp4 |
12.37MB |
7. Create a new user account in Microsoft 365.mp4 |
11.23MB |
7. Entering time.mp4 |
28.63MB |
7. Required Python Packages.html |
2.57KB |
7. Some Jupyter Notebook Commands.mp4 |
28.11MB |
7. What is a Schema.mp4 |
9.56MB |
7. What is Power Pivot.mp4 |
2.91MB |
8. Components of Power BI.mp4 |
8.73MB |
8. Database Schema.mp4 |
21.72MB |
8. How to enable Power Pivot.mp4 |
7.19MB |
8. Installing Python Packages.mp4 |
12.23MB |
8. Jupyter Notebook Components.mp4 |
21.42MB |
8. Undo and redo changes.mp4 |
27.88MB |
9.1 PrepPP.xlsx |
13.95MB |
9. Adding comments.mp4 |
19.10MB |
9. Create a data model.mp4 |
47.98MB |
9. Getting data into Power BI Desktop.mp4 |
27.49MB |
9. Import packages into a Python file.mp4 |
9.06MB |
9. MySQL Data Types.mp4 |
23.63MB |
9. The Notebook Dashboard.mp4 |
21.74MB |
averagerentalcostbyfilmcategory.py |
940B |
averagerentaldurationforfilmcategories.py |
881B |
Bonus Resources.txt |
386B |
comparerevenuefromdifferentfilmcategories.py |
1.05KB |
correlationsbetweenfilmlengthandrentalfrequency.py |
873B |
EV sales (King county).csv |
27.59MB |
Get Bonus Downloads Here.url |
183B |
mostfeaturedactorsinrentedfilm.py |
1.10KB |
popularcategoryrentedbycustomers.py |
953B |
rentalvolumeseasonaltrends.py |
801B |
sakilla_utils.py |
358B |