In this module, you will learn the basics of data analytics, namely, how to build visualizations. Using the Tableau service, you will create your first analytical dashboard.

Темы

• Introduction
• Netflix Cinematic Map
• Calculated Fields
• Creating Dashboards
• Summary

We are preparing for the next, more complex modules of the course.

Темы

• Productive Learning Tips
• Additional Tools

В рамках данного модуля ты ознакомишься с понятием базы данных и узнаешь, какие виды баз данных существуют. Также рассмотришь, каким образом хранятся данные в реляционных базах и научишься писать запросы SELECT, чтобы получать нужную информацию в желаемом виде. После завершения модуля ты будешь знать, что такое INNER JOIN и для чего он используется, будешь уметь сортировать и группировать данные по нужным критериям и применять различные функции конкретной БД. Итак, поехали!

Темы

• Introduction to SQL
• SELECT Statement
• WHERE Clause
• NULL Value, LIKE, BETWEEN, and IN Operators
• ORDER BY, LIMIT, DISTINCT Clauses
• Aliases
• Aggregate Functions
• GROUP BY Clause
• JOIN Clause
• Functions
• HAVING Clause

To work as a data analyst, you need in-depth knowledge of SQL. In this module, you will analyze sales and marketing indicators using a real database that contains data from an online store.

Темы

• Relational Databases
• Getting Started with Google BigQuery
• CASE WHEN
• UNION
• Subquery
• String Functions
• Datetime Functions
• Window Functions
• Common Table Expressions
• Additional Entities in SQL
• Nested Fields
• Query Optimization
• SQL and Additional Tools

In this module, you'll work with spreadsheets that are used to calculate, organize, analyze, and store data. You will learn how to process datasets, perform calculations using functions, and build pivot tables. You will also be able to visualize results in the form of graphs and charts.

Темы

• Spreadsheet — the Basic Tool for Analytics
• Data Importing
• Basic Data Types
• Formulas and Built-In Functions
• Cell Reference Types
• Data Cleaning
• Text Processing
• Working with Ranges
• Table Relationships
• Pivot Tables
• Data Visualization
• Data Exporting and Sharing
• Google Sheets Summary

Tableau is an entire ecosystem of interactive analytics. In this module, you'll learn how to connect data and create combined data sources, make complex visualizations, publish and update dashboards. You will also learn how to use Tableau Prep to prepare data, and Tableau Public and Tableau Online to share your work.

Темы

• Introduction
• Tableau Vocabulary
• Session Dashboard
• Sales Dashboard
• Email Dashboard
• Tableau Public Server Overview
• Tableau Desktop
• Tableau Online
• Tableau Prep
• Summary

Начинаем учить язык программирования Python! В этом модуле ты познакомишься с базовым синтаксисом, переменными, циклами, функциями, операторами, списками и с другими конструкциями Пайтон.

Темы

• Introduction
• Main Concepts
• Numbers
• Strings
• Boolean
• Lists
• Conditional Operators
• Loops
• Functions
• Summary

This module is designed to enhance your communication skills and overall soft skills. You’ll learn how to communicate effectively, feel confident during job interviews and public speaking, master techniques to manage stress, and much more. The best part? The module includes 28 practical tasks that will significantly boost your skills and help you see noticeable progress.

Темы

• Introduction to Communication & Stress Management
• Confidence Building and Stress Management
• Diction, Filler Words Reduction, and Body Language
• Public Speaking
• Job Interview
• Written Communication

Python is an extremely powerful tool for data analysis. You've already learned the basics, so we'll move on to introduce you to the NumPy and Pandas libraries for data processing and analysis. You'll also learn how to visualize your results with Matplotlib and Seaborn, and work with interactive environments like Jupyter Notebooks and Google Colab to perform and document your analytical tasks.

Темы

• Introduction
• Code Style
• Working With Numbers
• Working With Strings
• Dict Basics
• Functions Revisited
• Modules and Imports
• Environmental Setup for Data Analysis
• NumPy
• Pandas Part 1
• Pandas Part 2
• Visualisation with Matplotlib and Seaborn
• Connection to Database
• Exploratory Data Analysis

Statistics is a not an easy topic, but did our best to collect only the information that you will need to perform the real work tasks of a data analyst. In this module, you will learn the basics of statistics, including its role in business and everyday life. You will work on analyzing relationships between data, testing hypotheses, and you will learn to design of statistical experiments.

Темы

• Introduction to Statistics
• Descriptive Statistics
• Sampling: Approaches and Methods
• Statistical Hypotheses
• Relationship of Random Variables
• Design of Statistical Experiments

Let's start to develop product thinking. In this module, you'll learn approaches to hypothesis evaluation, such as A/B tests. You'll learn how to build product hypotheses, design A/B tests, choose metrics for conducting them, and analyze the results.

Темы

• A/B Testing Introduction
• Planning A/B Testing
• Data Collection and Analysis
• Creation of A/B Testing Tool
• Cases Analysis
• Advanced Tools and Approaches

We will create unique portfolio projects and place them on shared resources to demonstrate your skills to potential employers. We will also analyze the vacancies you can apply to upon course completion.

Темы

• Vacancies Overview
• Portfolio

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Темы

• Week 0: Team Project. Intro
• Week 1: Jira Environment
• Week 2: Status Check
• Week 3: Estimates
• Week 4: How to Demo Your Work
• Team Project for Employment
• Final Week: Retrospective

Ready to enter the tech market? Well... we'll get you ready — with a great resume, cover letter, a LinkedIn profile and mock interviews. Recruiters are in for a true discovery!

Темы

• Employment Roadmap
• Preparing Your Resume
• Interview Preparation
• Cover Letter Preparation
• Google, LinkedIn, DOU, Djinni
• How to Find and Apply for Vacancies
• Job Search Tips: Talking to Recruiters
• Work details FAQ

Let's dive into analytics. In this module, you'll learn how to forecast quantitative indicators using a linear multivariate model and a linear regression model with a single explanatory variable. You will master the concepts of training and test data, cross-validation, model quality measures, regularization, and forecasting qualitative indicators and risks using logistic regression. In addition, you will learn about cluster analysis, data clustering methods, similarity measures, and algorithms such as k-means, k-medians, and DBSCAN.

Темы

• Summary
• Cluster Analysis
• Feature Engineering Basics
• Categorical Values, Risks and Probabilities Forecasting
• Numerical Values Forecasting
• Advanced Analytics Introduction

Let's dive deeper into product thinking. In this module, you'll learn how to measure user engagement, activation, and retention. You will master typical product frameworks such as cohort analysis, RFM, NSM, and ARRR. You will also create a metrics map for a website as a project.

Темы

• Summary
• B2B Metrics
• Product Frameworks
• Monetization
• Product Metrics
• User Acquisition
• Introduction