Data analyst Course: From Zero to Hired
Data analyst Course From Zero to Hired
Perfect for newbies
90%
of our students start with no technical background
Course updated in 2024
100%
industry-relevant curriculum built to meet employer expectations
4,500+ employed grads
rating based on Google reviews
Data analyst: Salary
$1,750
+22%YoY salary growth. Source: DOU
Did you know?
Data Analysts use tools like SQL and Python to help companies make data-driven decisions. From updating pricing to launching features. The 2025 Future of Jobs Report says Data Analysts are among the fastest-growing jobs in the world. Now is a great time to join this booming field.
Employment in focus
We share the same goal — get you hired. With 20% theory and 80% practical tasks, we make it happen.
Market experts as your mentors
Mentors help you learn new topics, review your tasks, point out mistakes, and do live Q&A sessions.
Platform that has it all
Learn through tutorials, interactive tasks, AI quizzes, and group projects — all in one place.
Your perks in every course
Job Referrals
Get access to job openings from our partners before they hit the market.
English lessons
Gain skills to pass interviews and bond with your team.
Job search tips
Craft cover letters and resumes that land interviews.
Job tracker
Easily apply for jobs and track every step of your job hunt.
Mock interviews
Practice for real-world interviews and build your confidence.
*You can buy English lessons separately.
FORMAT COMPARISON
Which studying format suits you?
Weekdays, 9 am - 6 pm
In your free time
9-6 pm, Mon-Fri
Study at your own pace
Pay after you get a tech job
Get refunded if no tech job
This might be your CV
Marta K.
Data analyst
Skills
- Proficient in analyzing competitors and industry trends
- Experience researching data and user behavior patterns
- Skilled in creating and structuring data visualizations
- Ability to build and present dashboards and reports to stakeholders
- Knowledgeable in designing and implementing data workflows
- Capable of adapting data visualizations for different platforms
- Strong understanding of assessing data insights for specific audiences
- Experienced in using data metrics to inform business decisions
Technologies
90%
of Mate grads entered the tech field for the first time
What's covered
Course roadmap
Data Analytics Basics
5 topics
Course Fundamentals
2 topics
We are preparing for the next, more complex modules of the course.
Topics
- Productive Learning Tips
- Additional Tools
SQL Basics
11 topics
Semantically speaking, SQL closely resembles English, so you are in for a swift acquisition. We'll learn to use it with databases, to group, filter, sort and source data at wish.
Topics
- 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
SQL Advanced
13 topics
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.
Topics
- 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 Sheets for Data Analytics
13 topics
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.
Topics
- 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
10 topics
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.
Topics
- Introduction
- Tableau Vocabulary
- Session Dashboard
- Sales Dashboard
- Email Dashboard
- Tableau Public Server Overview
- Tableau Desktop
- Tableau Online
- Tableau Prep
- Summary
Python Basics
10 topics
Contrary to its name, there's nothing to be scared of, so let's approach Python head on. We'll start with strings, booleans, function, conditionals, loops and lists.
Topics
- Introduction
- Main Concepts
- Numbers
- Strings
- Boolean
- Lists
- Conditional Operators
- Loops
- Functions
- Summary
Communication and Stress Management
6 topics
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.
Topics
- Introduction to Communication & Stress Management
- Confidence Building and Stress Management
- Diction, Filler Words Reduction, and Body Language
- Public Speaking
- Job Interview
- Written Communication
Python for Data Analytics
14 topics
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.
Topics
- 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
6 topics
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.
Topics
- Introduction to Statistics
- Descriptive Statistics
- Sampling: Approaches and Methods
- Statistical Hypotheses
- Relationship of Random Variables
- Design of Statistical Experiments
Product A/B Testing
6 topics
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.
Topics
- 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
2 topics
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.
Topics
- Vacancies Overview
- Portfolio
Team Project
7 topics
In 4 weeks, you will create a product from scratch in teams with colleagues from other areas, following Scrum methodology, and present the results to your mates. In the end, you will have another project to add to your resume and gain invaluable real-world experience
Topics
- 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
Employment
8 topics
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!
Topics
- 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
Advanced Analytics: Prediction and Clustering Models
6 topics
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.
Topics
- Summary
- Cluster Analysis
- Feature Engineering Basics
- Categorical Values, Risks and Probabilities Forecasting
- Numerical Values Forecasting
- Advanced Analytics Introduction
Product and Marketing Metrics
7 topics
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.
Topics
- Summary
- B2B Metrics
- Product Frameworks
- Monetization
- Product Metrics
- User Acquisition
- Introduction
126
Topics
3
Projects
From zero to hired
What’s your path to becoming a Data analyst?
Land your job in tech
Start your new job as a Data analyst.
Book a call
Do I need a technical background? When can I start?
- We'll answer all your questions
- Help you choose the right course
- Provide exclusive offers
Skill level after the course
Mate graduates ace technical interviews
Who will guide you?
Coaches
Mentors
English Teachers
Education coordinators
Employment coordinators
Book a call
Let's get in touch
- We'll answer all your questions
- Help you choose the right course
- Provide exclusive offers
Faq
Have some more questions? We have the answers.
How do full-time and flexible formats differ?
In the full-time schedule, you study online from 9 AM to 6 PM, Monday to Friday. You’ll attend webinars, do practical tasks, and get help from mentors. There are group video calls four times a week in the afternoon. This intense schedule is not good if you want to work at the same time.
The flexible schedule lets you learn at your own pace. You decide when and how many hours to study. Mentors are available to help you, and you can chat and join video calls with classmates. Plus, you get lifetime access to the course, so you can learn whenever you want.
Can I fit studying at Mate with other activities?
In the flexible format, you can balance your studies with work or school. You set your own pace and receive support from our mentors throughout the course.
In the full-time format, it’s hard to combine studies with work or school due to its intensity. You’ll need to fully commit, studying from 9 am to 6 pm, Monday to Friday.
Will I get a certificate upon completion?
Sure! After finishing our course, you'll get a certificate. More than 4,300 of our graduates use it to show their skills on LinkedIn and other social media. But our main focus is helping you find a job, and we'll do everything we can to support you in that.
How do I choose a profession?
Do I need math or tech background to enroll?
No, you don’t need math or a technical background to enroll. In fact, 9 out of 10 Mate students come from non-technical backgrounds. Our job is to teach you the skills you need and help you land a job in tech.
How do I enroll?
To enroll in the full-time course, start by filling out an application and taking a short logic test with 15 questions. If your English level is below Pre-intermediate, we'll ask you to make a short video about yourself. Once we check that your English is good enough for learning, you can move on with your enrollment and set up an interview with our manager.
For the flexible course, just send an application. Our manager will reach out to explain the course details and help you pick the best option. You’ll get access to the course right after you pay.
Are there any age limits for this course?
You can apply for the full-time course starting at age 16 with your parents' permission. For the flexible course, you can begin if you’re at least 15 years old.
The employment guarantee applies if you reach the legal working age in your country by the time you finish the course.
How are you so sure that l'll find a job?
For over 10 years, we’ve been helping people kickstart their tech careers — and we’ve gotten pretty good at it.
Our courses are built around what companies actually want, with tons of hands-on practice to get you job-ready. And you’re never on your own — we’ll guide you every step of the way, from polishing your resume to nailing your interviews.
The best part? 80% of our grads land a tech job just a few months after finishing the course.
How does money-back guarantee work?
For full-time graduates, you only start paying for your education after finding a tech job. The payment is 12% of your net salary for 36 months. If you don’t get a job, you pay nothing.
If you finish the flexible course, actively search for a job with our support for 16 weeks, and don't receive any offers, you can get a full refund.
What's the schedule on full-time?
The full-time schedule combines theory lessons, practice, and Q&A sessions:
9:00 AM - 10:00 AM — Algorithms 10:00 AM - 11:30 AM — Theory 11:30 AM - 12:30 PM — Break 12:30 PM - 2:00 PM — Practice 2:00 PM - 2:30 PM — Q&A session 2:30 PM - 5:00 PM — Practice 5:00 PM - 6:00 PM — Q&A session
What jobs can I get after finishing the course?
Graduates of the Data Analytics course most often get their first job in the following positions: Junior Data Analyst, Product Analyst, Business Analyst, Junior Data Scientist, BI Analyst, and Marketing Analyst.
