Курс Data Analyst

На курсі Data Analytics ти опануєш всі потрібні технології, щоб стати Data-аналітиком. Ти опануєш такі технології, як SQL, Python, Tableau, статистика, A/B тестування, метрики продукту і маркетингу, і багато чого іншого.

Програма курсу

Data Analytics Basics

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

Course Fundamentals

Productive Learning Tips.

SQL Basics

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

SQL Advanced

• 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

Google Spreadsheets for Data Analyst

• 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 Shiring
• Google Sheets Summary

Tableau

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

Python Basics

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

Python for Data Analytics

• Introduction
• Code Style
• Working With Numbers
• Working With Strings
• Dics 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

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

Product A/B Testing

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

Building Portfolio

• Portfolio
• Vacancies Overview

Employment 2.0

• Employment Roadmap
• Preparing Your Resume
• Interview Preparation
• Cover Latter Preparation
• Google, LinkedIn, DOU, Djinni
• How to find and apply for vacancies
• Job Search Tips: Talking to Recruiters
• Work details FAQ

Advanced Analytics: Prediction and Clustering Models

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

Product and Marketing Metrics

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

Особливості курсу

• Працюєш? Вчись у власному темпі
• Зідзвони з менторами двічі на тиждень
• Чат з одногрупниками
• Навчальні матеріали "без води" замість довгих лекцій
• Гарантуємо працевлаштування після навчання