Marketing analyst from zero to middle - course 96,300 rub. from Netology, training 14 months, Date November 29, 2023.

Analytics expert, consultant, ex-CAO Alfa Capital, Biglion, Broccoli, Utkonos.

Analytical thinking
Learn to think like an analyst and formulate hypotheses to test. You will understand that analytics is built around data. Get acquainted with the basic analytics tool and be able to conduct simple data analysis in it.
• What is analytical thinking
• Introduction to Google Sheets
• Advanced Google Sheets
• Basic statistics
• Where does the data come from?
• Advanced data visualization
• Python as a data analysis tool
• Machine learning for life

Yandex capabilities. Metrics
Find out how Yandex works. Metrica, learn how to create and configure a Yandex counter. Metrics, set goals, configure notifications and access. You will understand the types of reports and click maps, scrolling, and web viewer.
• Pros and cons of Yandex. Metrics
• How Yandex works. Metrics
• Creating and setting up a Yandex counter. Metrics
• Goals in Yandex. Metrica
• Filters and operations
• Parameters of visitors and visits
• Python as a data analysis tool
• Key Yandex reports. Metrics
• Summaries

Google Analytics Features
Consider the methods of data transfer and processing logic in Google Analytics. Learn how to install a Google Analytics counter on your website and set up goals and events. Learn how to see data sampling in reports. Understand standard and custom Google Analytics reports.
• What is Google Analytics
• Methods of transmission and logic of data processing in Google Analytics
• Account structure. Settings for resource, view, channel groups, content groups and alerts
• Segments and filters: for what tasks and what is best to use
• Implementation of advanced electronic commerce and interpretation of reports based on it
• Measurement Protocol as a method of transmitting data to Google Analytics about sales or any other interactions with customers

Metrics, hypotheses, growth points
Get acquainted with business indicators. Learn how to develop and optimize reporting. You will understand what a data-driven approach to decision making is.
• Understanding business goals
• Financial metrics
• Marketing and product metrics
• Hierarchy of metrics
• Requirements collection and reporting development
• Formulation of hypotheses
• Test design, implementation and analysis. Building simple models
• Optimization of reporting

Building end-to-end analytics
You will learn how to correctly evaluate the effectiveness of advertising, which advertising channels bring in money and which only waste the budget, how much the company actually earned during promotion.
• Review of steps: sales funnel and its metrics
• Interaction between the marketing department and the sales department. CRM. Call tracking
• Omnichannel for different types of businesses and sites, integration with various systems
• Product marketing and unit economics
• Hypothesis testing and customer return tools
• RFM analysis, loyalty program
• Cohort reports in marketing and cases

R for data analysis
Learn to solve work problems in an efficient and reproducible way - write code for reuse, automate the creation of reports. You will practice using basic R packages to manipulate data, create graphs, and perform statistical analysis.
• Overview of R, basic programming principles
• Working with data sets. Different data sources and connecting to them
• Visualization in R - exploring data using charts
• Stages of data analysis. Data preparation and cleaning
• Basics of modeling in R
• Providing analysis results. Advanced Visualization
• Development of analytical web applications in R (Shiny)

Python for data analysis
You'll learn how to use basic tools and approaches in Python to get started working with data. Review the basics of linear algebra, set theory, mathematical optimization techniques, descriptive statistics, statistical data analysis, and learn how to implement it in Python.
• Introduction to Git
• Python Basics. Control constructs and collections
• Functions
• Working with the file system and modules
• Regular expressions and parsing basics
• Exceptions and error handling
• Concept of class
• numpy library. Computational tasks
• Pandas library
• Functions and data handling
• Basics of parsing and working with APIs
• Advanced pandas

Visualization in Power BI
You will be able to determine key product metrics without programming and create dashboards. You will understand how to optimize your sales funnel and improve your customer experience.
• Loading and converting data
• Data analysis
• Data visualization. Working with reports
• Publishing data and collaborating with reports
• Integration with services

Tableau: Create by exploring data
Learn to process data in real time, generate clear and visual reports on key indicators.
• Familiarity with Tableau infrastructure. Loading data. First dashboard
• Main types of visualizations. Visualization best practices
• Basics of working with calculation fields, filters, sets and groupings
• Using parameters, combining multiple sources
• Complex calculation fields, overview of main groups of functions
• LOD, Set Actions, Parameter Actions functions
• Development of dashboards. Setting up interaction between visualizations
• Tableau Professional. Connecting to SQL Databases
• Tableau Server Basics

Graduate work
In your thesis, you will develop a plan to change the marketing strategy of your project, based on the data collected and analyzed during your studies.