Meta Marketing Analytics Professional Certificate
Courses Weekly Breakdown
Coursera Study Guide
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Courses Weekly Breakdown
TABLE OF CONTENT
- COURSE 1: MARKETING ANALYTICS FOUNDATION
- COURSE 2: INTRODUCTION TO DATA ANALYTICS
- COURSE 3: STATISTICS FOR MARKETING
- COURSE 4: DATA ANALYTICS METHODS FOR MARKETING
- COURSE 5: MARKETING ANALYTICS WITH META
- COURSE 6: META MARKETING SCIENCE CERTIFICATION EXAM
Meta Marketing Analytics Answers – Courses & Study Guide
COURSE 1: Marketing Analytics Foundation
By the end of this course you will be able to:
• Describe how data and measurement inform a marketing action
• Describe the basic principles of marketing
• Identify why measurement and analytics matter in digital marketing
• Describe how data is collected and related to digital marketing
• Explain the significance of the privacy regulations that govern the online marketing space
• Describe the Meta pixel and how it is created on the Meta platform
• Describe how information is recorded on mobile devices
• Explain how an API connects data captured offline to an online platform
• Describe common platforms for online data management and evaluation
• Navigate Google Analytics and Meta Ads Manager reports
COURSE 2: Introduction to Data Analytics
By the end of this course, you will be able to:
• State business goals, KPIs and associated metrics
• Apply a Data Analysis Process: OSEMN
• Identify and define the relevant data to be collected for marketing
• Compare and contrast the different formats and use cases of different kinds of data
• Identify gaps in data collected and describe the strengths and weaknesses
• Demonstrate proficiency in Python with variables, control flow, loops, and basic data structures
• Sort, query and structure data in spreadsheets and with Python libraries
• Write basic SQL statements to select, group and filter data
• Visualize data patterns and trends with spreadsheets
• Utilize Tableau to visualize data patterns and trends
- Week 1: Working with Data
- Week 2: Python for Data Analysis
- Week 3: Data Cleaning and Processing
- Week 4: Introduction to Data Visualization
- Week 5: Structuring Real-World Analytics Projects (No Quizzes/Practice Test)
COURSE 3: Statistics for Marketing
By the end of this course you will be able to:
• Understand the concept of dependent and independent variables
• Identify variables to test
• Understand the Null Hypothesis, P-Values, and their role in testing hypotheses
• Formulate a hypothesis and align hypotheses with business goals
• Identify actions based on hypothesis validation/invalidation
• Explain Descriptive Statistics (mean, median, standard deviation, distribution) and their use cases
• Understand basic concepts from Inferential Statistics
• Explain the different levels of analytics (descriptive, predictive, prescriptive) in the context of marketing
• Create basic statistical models for regression using data
• Create time-series forecasts using historical data and basic statistical models
• Understand the basic assumptions, use cases, and limitations of Linear Regression
• Fit a linear regression model to a dataset and interpret the output using Tableau and statsmodels
• Explain the difference between linear and multivariate regression
• Run a segmentation (cluster) analysis
• Describe the difference between observational methods and experiments
COURSE 4: Data Analytics Methods for Marketing
By the end of this course you will be able to:
• Describe when analytics is most commonly used in marketing
• Understand your audience using analytics and variable descriptions
• Segment a population into different audiences using cluster analysis
• Use historical data to plan your marketing across different channels
• Use linear regression to forecast marketing outcomes
• Describe marketing mix modeling
• Describe attribution modeling
• Apply different attribution models
• Evaluate advertising effectiveness and describe the shortcomings
• Describe the use of experiments to evaluate advertising effectiveness
• Explain how A/B testing works and how you can use it to optimize ads
• Evaluate results of an experiment and assess the strength of the experiment
• Evaluate and optimize your sales funnel
COURSE 5: Marketing Analytics with Meta
By the end of this course you will be able to:
• Describe how an ad is created and delivered in Meta Ads Manager
• Evaluate campaign results
• Conduct an A/B Test
• Evaluate advertising effectiveness with Conversion Lift Tests
• Evaluate advertising effectiveness with Brand Lift tests
• Choose the best approach to evaluating advertising effectiveness given a scenario
• Explain how and when to apply Marketing Mix Modeling
• Choose the best approach to optimizing your marketing mix given a scenario
• Implement a full analysis process from the formulation of a hypothesis to recommending measurement solutions, performing an analysis, generating insights and presenting results and recommendations
COURSE 6: Meta Marketing Science Certification Exam
This course helps you prepare for the Meta Marketing Science Certification exam. You’ll be guided through scheduling and taking the exam through Meta Blueprint. You’ll get access to the study guide and other resources to help you prepare to take the exam.
- Week 1: Prepare for and take the Meta Marketing Science Certification Exam
- Week 2: Career Support and Congratulations!
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