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[ FreeCourseWeb com ] Udemy - Data Science in Marketing An Introduction Course 2021
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1. Introduction
1. Course structure.mp4
1. Course structure.srt
10. Applying Data Transformation.mp4
10. Applying Data Transformation.srt
10.1 Applying_Data_Transformation.ipynb
2. How To Make The Most Out Of This Course.mp4
2. How To Make The Most Out Of This Course.srt
3. Important note on tool.mp4
3. Important note on tool.srt
4. Introduction to Data Models and Structured Data.mp4
4. Introduction to Data Models and Structured Data.srt
5. Introduction to Pandas.mp4
5. Introduction to Pandas.srt
6. Importing JSON Files into pandas.mp4
6. Importing JSON Files into pandas.srt
6.1 Importing_JSON_Files_into_pandas.ipynb
7. Identifying Semi-Structured and Unstructured Data.mp4
7. Identifying Semi-Structured and Unstructured Data.srt
7.1 Identifying_Semi_Structured_and_Unstructured_Data.ipynb
8. Creating and Modifying Test Dataframes.mp4
8. Creating and Modifying Test Dataframes.srt
8.1 Creating_and_modifying_Test_dataframes.ipynb
9. Combining DataFrame and Handling Missing Values.mp4
9. Combining DataFrame and Handling Missing Values.srt
9.1 Combining_DataFrames_and_Handling_Missing_Values.ipynb
Marketing_Course_With_Data_Science_Part1
data.csv
sales.xlsx
user_info.json
2. Key Performance Indicators and Visualizations
1. Data Science and Marketing.mp4
1. Data Science and Marketing.srt
2. Introduction to Key Performance Indicators and Visualizations.mp4
2. Introduction to Key Performance Indicators and Visualizations.srt
3. Computing and visualizing KPIs.mp4
3. Computing and visualizing KPIs.srt
3.1 bank-additional-full.csv
4. Aggregate conversion rate.mp4
4. Aggregate conversion rate.srt
4.1 Computing_and_visualizing_KPIs.ipynb
5. Conversion rates by age.mp4
5. Conversion rates by age.srt
5.1 Computing_and_visualizing_KPIs (1).ipynb
6. Conversion vs non-conversion.mp4
6. Conversion vs non-conversion.srt
6.1 Computing_and_visualizing_KPIs (2).ipynb
7. Conversions by age and marital status.mp4
7. Conversions by age and marital status.srt
7.1 Computing_and_visualizing_KPIs (3).ipynb
8. Summary of the section.mp4
8. Summary of the section.srt
3. From engagement to conversion
1. Introduction.mp4
1. Introduction.srt
10. Interpreting Decision Tree.mp4
10. Interpreting Decision Tree.srt
11. Summary of the project.mp4
11. Summary of the project.srt
2. Decision trees and interpretations.mp4
2. Decision trees and interpretations.srt
2.2 From_Engagement_to_Conversions.ipynb
3. Conversion rates by job.mp4
3. Conversion rates by job.srt
3.1 From_Engagement_to_Conversions (1).ipynb
4. Default Rates by Conversions.mp4
4. Default Rates by Conversions.srt
4.1 From_Engagement_to_Conversions (2).ipynb
5. Bank balances by conversions and Conversion rates by number of contacts.mp4
5. Bank balances by conversions and Conversion rates by number of contacts.srt
5.1 From_Engagement_to_Conversions (3).ipynb
6. Encoding Months.mp4
6. Encoding Months.srt
6.1 From_Engagement_to_Conversions (4).ipynb
7. Encoding Jobs.mp4
7. Encoding Jobs.srt
7.1 From_Engagement_to_Conversions (5).ipynb
8. Encoding marital and the housing and loan variables.mp4
8. Encoding marital and the housing and loan variables.srt
8.1 From_Engagement_to_Conversions (6).ipynb
9. Building decision trees.mp4
9. Building decision trees.srt
9.1 From_Engagement_to_Conversions (7).ipynb
bank-full.csv
bank-names.txt
bank.csv
4. Product analytics
1. Introduction.mp4
1. Introduction.srt
2. Product analytics Implementation Part 1.mp4
2. Product analytics Implementation Part 1.srt
2.1 Online Retail.xlsx
3. Product analytics Implementation Part 2.mp4
3. Product analytics Implementation Part 2.srt
3.1 Product_Analytics_Implementation.ipynb
4. Repeat customers Implementation.mp4
4. Repeat customers Implementation.srt
5. Repeat customers Implementation Part 2.mp4
5. Repeat customers Implementation Part 2.srt
5.1 Product_Analytics_Implementation.ipynb
6. Trending Items over time.mp4
6. Trending Items over time.srt
6.1 Product_Analytics_Implementation.ipynb
7. Trending Items over time Implementation.mp4
7. Trending Items over time Implementation.srt
8. Analysing Results.mp4
8. Analysing Results.srt
5. Product Recommender System
1. Introduction.mp4
1. Introduction.srt
2. Data Preperation.mp4
2. Data Preperation.srt
2.1 Product_Recommendation_System.ipynb
3. Building a customer-item matrix.mp4
3. Building a customer-item matrix.srt
3.1 Product_Recommendation_System (1).ipynb
4. Collaborative Filtering.mp4
4. Collaborative Filtering.srt
4.1 Product_Recommendation_System (3).ipynb
5. Item-based product recommendation Part 1.mp4
5. Item-based product recommendation Part 1.srt
5.1 Product_Recommendation_System (4).ipynb
6. Item-based product recommendation Part 2.mp4
6. Item-based product recommendation Part 2.srt
6.1 Product_Recommendation_System (5).ipynb
6. Customer Lifetime Value
1. Introduction.mp4
1. Introduction.srt
2. Data Clean-Up.mp4
2. Data Clean-Up.srt
2.1 Customer_Lifetime_Value.ipynb
3. Data Analysis Part 1.mp4
3. Data Analysis Part 1.srt
3.1 Customer_Lifetime_Value (1).ipynb
4. Data Analysis Part 2.mp4
4. Data Analysis Part 2.srt
4.1 Customer_Lifetime_Value (2).ipynb
5. Data preparation Part 1.mp4
5. Data preparation Part 1.srt
5.1 Customer_Lifetime_Value (3).ipynb
6. Data preparation Part 2.mp4
6. Data preparation Part 2.srt
6.1 Customer_Lifetime_Value (4).ipynb
7. Data preparation Part 3.mp4
7. Data preparation Part 3.srt
7.1 Customer_Lifetime_Value (6).ipynb
8. Building Linear Regression Model.mp4
8. Building Linear Regression Model.srt
8.1 Customer_Lifetime_Value (7).ipynb
9. Evaluating Model Performance.mp4
9. Evaluating Model Performance.srt
9.1 Customer_Lifetime_Value (8).ipynb
7. Data-Driven Customer Segmentation
1. Introduction.mp4
1. Introduction.srt
2. Data Cleanup.mp4
2. Data Cleanup.srt
2.1 Data_Driven_Customer_Segmentation.ipynb
3. K-means Clustering.mp4
3. K-means Clustering.srt
3.1 Data_Driven_Customer_Segmentation (1).ipynb
4. Selecting the best number of clusters.mp4
4. Selecting the best number of clusters.srt
4.1 Data_Driven_Customer_Segmentation (2).ipynb
5. Interpreting customer segments.mp4
5. Interpreting customer segments.srt
5.1 Data_Driven_Customer_Segmentation (3).ipynb
8. Thank you
1. Thank you.mp4
1. Thank you.srt
Bonus Resources.txt
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