Linkedin - Python for Marketing
Linkedin - Python for Marketing
Code:
Title: Python for Marketing Publisher: Linkedin.Learning Size: 310M (324943479 B) Files: 7F Date: 11/12/2019 Course #: Linkedin.Learning Type: N/A Published: November 12, 2019 Modified: N/A URL: www.linkedin.com/learning/python-for-marketing Author: Nick Duddy Duration: Skill: Intermediate Exer/Code: [X] Description: Take your marketing analytics to the next level with Python. The features that make Python so useful for data scientists are the same ones that marketers can use to better understand their customers, product performance, competition, and marketplace. In this course from Madecraft, you can learn how to use Python to improve marketing at your business. Discover how to import and clean data from sources like Google Analytics and Facebook, merge data sets, create detailed visualizations, analyze time series data, and build custom metrics and alerts for your marketing activities. Instructor Nick Duddy shows how to combine these techniquesΓÇöand helpful Python libraries like Pandas and SeabornΓÇöto conduct market analysis, predict consumer behavior, assess the competition, monitor market trends, and more.
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Other /Tutorials
309.9 MB
Linkedin - Python for Marketing
01 - Introduction
01 - Accelerate your marketing with Python.mp4 (3.8 MB)
01 - Accelerate your marketing with Python.srt (2.1 KB)
02 - The Role of Python in Marketing
01 - Prerequisites.mp4 (1,022.0 KB)
02 - Why Python is great for marketers.mp4 (3.5 MB)
02 - Why Python is great for marketers.srt (2.4 KB)
03 - Why Python is valuable for marketers.mp4 (2.1 MB)
03 - Loading and Exploring Your Data
01 - Introduction to pandas.mp4 (3.1 MB)
02 - Installing Jupyter.mp4 (4.0 MB)
03 - Importing Google Analytics data.mp4 (15.8 MB)
03 - Importing Google Analytics data.srt (6.8 KB)
04 - Importing Google Search Console data.mp4 (2.9 MB)
05 - Importing Facebook and AdWords data.mp4 (8.4 MB)
05 - Importing Facebook and AdWords data.srt (3.7 KB)
06 - Accessing the Google Trends API.mp4 (6.3 MB)
06 - Accessing the Google Trends API.srt (3.2 KB)
07 - Visualizing Google data.mp4 (7.2 MB)
07 - Visualizing Google data.srt (4.1 KB)
08 - Plotting Facebook and Google Ads data.mp4 (9.5 MB)
08 - Plotting Facebook and Google Ads data.srt (5.0 KB)
09 - Visualizing Google Trends data.mp4 (4.3 MB)
09 - Visualizing Google Trends data.srt (2.2 KB)
04 - Cleaning, Wrangling, and Joining Your Data
01 - Introduction to data wrangling.mp4 (2.2 MB)
02 - Fixing Google Analytics page data.mp4 (11.6 MB)
02 - Fixing Google Analytics page data.srt (6.2 KB)
03 - Preparing data to be grouped.mp4 (7.7 MB)
03 - Preparing data to be grouped.srt (3.5 KB)
04 - Creating new datasets with Groupby.mp4 (9.3 MB)
04 - Creating new datasets with Groupby.srt (4.8 KB)
05 - Rebuilding Google Analytics data.mp4 (9.9 MB)
06 - Dropping columns.mp4 (6.3 MB)
07 - Replacing missing Facebook Ad data.mp4 (3.5 MB)
07 - Replacing missing Facebook Ad data.srt (1.7 KB)
08 - Merging Google Analytics and Search Console.mp4 (4.8 MB)
09 - Saving your data to a CSV.mp4 (2.1 MB)
05 - Visualizing Marketing Data in Python
01 - Custom visualizations in Python.mp4 (1.9 MB)
01 - Custom visualizations in Python.srt (1.2 KB)
02 - Import, explore, and plot a basic chart.mp4 (13.1 MB)
02 - Import, explore, and plot a basic chart.srt (7.0 KB)
03 - Creating Matplotlib subplots.mp4 (7.2 MB)
04 - Plotting a secondary y-axis.mp4 (7.1 MB)
04 - Plotting a secondary y-axis.srt (4.0 KB)
05 - Adding x and y labels to a plot.mp4 (8.0 MB)
05 - Adding x and y labels to a plot.srt (4.2 KB)
06 - Rotating xticks labels on plot.mp4 (6.5 MB)
07 - Adding a legend to a plot.mp4 (4.0 MB)
08 - Adding a title to your plot.mp4 (4.1 MB)
09 - Adding annotations to plots.mp4 (9.3 MB)
09 - Adding annotations to plots.srt (4.7 KB)
10 - Switching between Matplotlib styles.mp4 (4.2 MB)
10 - Switching between Matplotlib styles.srt (1.6 KB)
11 - Using a scatter plot in Seaborn.mp4 (3.0 MB)
12 - Customizing a scatter plot in Seaborn.mp4 (7.1 MB)
13 - Creating a Facebook Ads heatmap in Seaborn.mp4 (9.7 MB)
13 - Creating a Facebook Ads heatmap in Seaborn.srt (4.6 KB)
06 - Working with Timeseries
01 - Time series notebook.mp4 (1.3 MB)
01 - Time series notebook.srt (0.8 KB)
02 - Fixing missing values.mp4 (9.6 MB)
03 - Resampling time series data.mp4 (4.9 MB)
03 - Resampling time series data.srt (3.0 KB)
04 - Rolling average plots.mp4 (8.9 MB)
04 - Rolling average plots.srt (4.2 KB)
05 - Plotting weekly PPC and CPC data.mp4 (5.4 MB)
06 - Adding dynamic annotations to a plot.mp4 (8.8 MB)
07 - Calculating, Filtering, and Creating New Metrics
01 - Introduction to calculating and filtering.mp4 (1.5 MB)
01 - Introduction to calculating and filtering.srt (1.1 KB)
02 - Calculating metrics.mp4 (13.4 MB)
03 - Filtering data.mp4 (11.5 MB)
03 - Filtering data.srt (5.4 KB)
08 - Creating Helpful Alerts
01 - Intro to alert calculations.mp4 (598.5 KB)
01 - Intro to alert calculations.srt (0.5 KB)
02 - Creating simple alerts.mp4 (4.8 MB)
02 - Creating simple alerts.srt (2.4 KB)
03 - Calculating two date ranges.mp4 (7.7 MB)
04 - Creating alerts with actions.mp4 (11.5 MB)
04 - Creating alerts with actions.srt (6.1 KB)
09 - Conclusion
01 - Next steps.mp4 (3.6 MB)
Exercise Files
Ex_Files_Python_Marketing.zip (1.8 MB)
files
2019-11-15 20:07:01
English
Seeders : 11 , Leechers : 2
Linkedin Python Marketing
Linkedin - Python for Marketing
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