Python for Marketing
Python for Marketing
What you’ll learn
Skills you’ll gain
This course is your gateway to succeeding in marketing in the digital era, all through the lens of Python. Imagine effortlessly loading and scrubbing marketing datasets, then diving deep into the numbers to unearth game-changing insights. You'll get hands-on with data manipulation, tweaking and twisting your data until it reveals those hidden marketing gems. Then, it's showtime: you'll bring your data to life with stunning visualizations that tell compelling stories, making your insights pop off the page. In addition, you'll learn how to automate personalized campaigns and explore new market opportunities. Lavanya Vijayan has designed this course to not just teach you Python for marketing, but to transform the way you think about and execute data-driven strategies. Ready to let Python turbocharge your marketing strategies? Let go!
Syllabus
Download syllabus-
1
Identify the role of Python in marketing Python and data play a pivotal role in modern marketing, offering tools for efficient analysis and decision-making. 1m
-
2
Load marketing data in Python Loading marketing data into a programming environment is the first step towards unlocking insights. 2m
-
3
Interpret marketing data in Python Interpreting marketing data is crucial for making informed decisions, and Python provides the tools for insightful data analysis. 3m
-
1
Clean marketing data in Python Clean data is fundamental for accurate analysis, and Python offers powerful techniques for cleaning marketing datasets. 2m
-
2
Handle missing values in marketing data Missing values can impact the reliability of marketing analysis, and Python provides efficient methods for handling them. 2m
-
3
Prepare for outlier handling in Python Outliers can skew marketing insights, and Python equips marketers with techniques to handle them effectively. 2m
-
4
Handle outliers in marketing data There are many ways to define and address outliers in datasets. 4m
-
5
Reformat marketing data in Python Properly formatted data is essential for effective analysis, and Python provides tools to reformat data as needed. 3m
-
1
Manipulate marketing data in Python Python data manipulation capabilities empower marketers to transform and shape data to meet specific analysis requirements. 3m
-
2
Group marketing data by categories Grouping data is essential for aggregating insights by categories, and Python facilitates this process for marketers. 3m
-
3
Merge marketing datasets in Python Combining datasets enhances the depth of marketing analysis, and Python provides tools for data joining. 1m
-
4
Filter marketing datasets in Python Effective analysis often requires focused datasets, and Python offers robust filtering mechanisms. 2m
-
5
Export marketing data as CSV Sharing and collaborating with marketing data is simplified by exporting data to common file formats, and Python makes this process straightforward. 1m
-
1
Visualize marketing data in Python Visualization is a powerful tool for conveying complex marketing insights, and Python's libraries enable informative visualizations. 1m
-
2
Create a bar plot in Python Bar plots are a fundamental visualization type for marketing data presentations, and Python allows marketers to easily create them. 2m
-
3
Label the axes in data visualization Clear labeling enhances the readability of data visualizations. 3m
-
4
Add a title to your data visualization Adding a title makes your data visualizations easier to understand. 1m
-
5
Use subplots for multiple visualizations Subplots allow for the simultaneous presentation of multiple visualizations, providing a comprehensive view of marketing data. 2m
-
6
Add a secondary y-axis to your data visualization Multiple y-axes accommodate diverse data ranges within a single visualization, enhancing the depth of insights. 2m
-
7
Add a legend to your data visualization Legends help convey how data points have been visually grouped in a chart, including by color, shape, and more. 1m
-
8
Annotate your data visualization Annotations can be placed directly on a data visualization, providing additional information that enriches the audience's understanding. 2m
-
9
Customize a scatter plot in Python Scatter plots are versatile for displaying relationships between numerical variables, and Python allows for customization of these plots. 2m
-
10
Create a heatmap in Python Heatmaps provide a visual representation of data density, aiding in the identification of patterns and trends. 2m
-
1
Find value of time series data in marketing Time series data is integral for understanding trends and patterns in marketing, guiding timely decision-making. 1m
-
2
Prepare the times series data for analysis Data preprocessing is key for effective time series analysis, and Python provides tools to preprocess time series data. 4m
-
3
Resample the time series data Resampling time series data allows for adjustments in granularity, facilitating trend identification and analysis. 3m
-
4
Create a rolling average plot for time series marketing data A rolling average plot offers a smoothed view of time series trends, aiding in identifying patterns and fluctuations. 3m
-
5
Plot cost-per-click marketing data Visualizing cost-per-click (CPC) data is essential for evaluating advertising expenses and making informed budgeting decisions. 3m
-
6
Add dynamic annotations Dynamic annotations enhance data visualizations and provide additional context to data points. 4m
-
1
Calculate click-through rate in Python Click-through rate (CTR) is a vital metric for measuring user engagement, and Python provides the tools for its calculation. 2m
-
2
Calculate bounce rate in Python Bounce rate is a key indicator of website engagement, and Python facilitates its calculation for effective performance analysis. 2m
-
3
Calculate key performance indicators Key performance indicators (KPIs) provide actionable insights into marketing effectiveness, and Python supports their calculation. 3m
-
4
Create new metrics for marketing reports Custom metrics tailored to specific business objectives enhance the depth and relevance of marketing reports. 5m
-
1
Send personalized emails using Python Personalized communication is key to effective marketing, and Python enables the automation of personalized email campaigns. 5m
-
2
Set up helpful alerts with Python Proactive alerts can prevent issues and ensure timely responses in marketing, and Python supports their implementation. 2m
-
3
Web scraping for marketing insights Web scraping allows you to extract valuable external data, enriching marketing analyses and strategies. 1m
-
1
Unlock resources and next steps Congratulations on completing this course! 1m
Certificate
Certificate of Completion
Awarded upon successful completion of the course.
Instructor
Lavanya Vijayan
Lavanya Vijayan is a Technical Curriculum Architect and Data Science Instructor at Madecraft. Lavanya has authored several programming and data science courses for LinkedIn Learning. She has also developed technical curriculum for Google’s Advanced Data Analytics and Cybersecurity career certifications.
Lavanya has a Master’s degree in Information and Data Science from UC Berkeley.
Lavanya Vijayan
Technical Curriculum Architect and Data Science Instructor
Accreditations
Link to awards
How GoSkills helped Chris
I got the promotion largely because of the skills I could develop, thanks to the GoSkills courses I took. I set aside at least 30 minutes daily to invest in myself and my professional growth. Seeing how much this has helped me become a more efficient employee is a big motivation.
