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Data Science
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Data Analytics Full Course
Why participate in the "Data Analytics Full Course"? Data analytics is applied in many fields of any business that has data. It empowers companies to make efficient decisions rega...
What you'll gain
- ✓ Basic knowledge on Excel
- ✓ Advanced knowledge on Excel
- ✓ Power BI & Intro to Tableau
- ✓ Data driven decision making
✓ Free consultation · Certificate on completion · Practical learning · Certificate-ready · BDG since 2009
Duration
5 months
Format
Offline
Level
Beginner
Starts
Aug 21, 2026
Certificate
On completion
Schedule
- Monday · 19:30–21:30
- Friday · 19:30–21:30
The BDG ecosystem
More than a course
At BDG, learning continues beyond lessons. You get access to guidance, community, events, spaces, and resources that support your professional growth.
Personal Branding
Learn how to present your skills, build professional visibility, and create a stronger personal brand in your field.
Free Webinars & Seminars
Join free webinars, seminars, and open sessions every month to keep learning, meet experts, and discover new opportunities.
Big Community
Become part of a large professional community of students, graduates, trainers, and industry specialists.
Coworking Spaces
Use BDG spaces for learning, networking, teamwork, and focused work when you need the right environment to grow.
Library
Access useful books, materials, guides, and learning resources selected to support your development.
Who can you become?
Why participate in the "Data Analytics Full Course"?
Data analytics is applied in many fields of any business that has data. It empowers companies to make efficient decisions regarding their strategy and tactics, analyzing market demand, customers, competitors, and other available data. The course is designed for complete training in data analysis, during which you will learn for 5 months how to collect and analyze data, as well as how to automate these processes. The course is based on practical projects, which you will carry out with specialists with many years of experience in the fields of finance, economics, and tech industry. The "Data Analytics Full Course" helps also to develop your analytical and mathematical skills, At the end of the course, you will acquire data analysis, collection, and evaluation skills, and master the necessary tools (Excel, SQL, Power BI, Tableau, Python, etc.), to start your career as a junior Data analyst.Get 5% Cashback
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Who is this course for
-
✓
Beginners
If you have a career in finance, IT, or related fields and are interested in data collection and analysis, the course is a great start to a new, modern, and in-demand career. It will help you master the complete skills to start your first job in this field in just 5 months.
-
✓
Specialists from other industries
The course content is adapted to start from scratch and develop your skills during the course. So, if you have a different profession or job, but think about starting a career in Data analytics, this course is a good choice for you.
What you will learn
- ✓Basic knowledge on Excel
- ✓Advanced knowledge on Excel
- ✓Power BI & Intro to Tableau
- ✓Data driven decision making
- ✓SQL for Data Analytics
- ✓Automating Data Analytics with Python
Program
- Course Introduction
- Data Analytics in Different Sectors
Calculation and Tables, Home Tab
Page Layout, Review, View
Most frequently used functions
- Spreadsheet analytical techniques: Overview
- The Fill Handle & Autocorrect
- Data Validation
- Conditional Formatting
Circular References: Iterations
- What-If Controls: The Goal Seek Command & Solver: Introduction
- What-If Controls: One & Two-Dimensional Data Tables
- What-If Controls: Using the Scenario Manager for Sensitivity Analysis
- Charts & Graphics: Plotting Data
- Combining Chart Types: Falling ball speed
- Measures of Central Tendency, Asymmetry, and Variability
- Correlation & Predictability
- Integration & Differentiation
- Regression and Curve Fitting
- Multiple Regression: Linear Estimates
- Nonlinear Regression, Dealing with Categorical Data
- Confidence Intervals & Hypothesis Testing
- Linear algebra: Reiterations and Matrixes
- Linear algebra: Solving Equations
- Types of Distributions: Sampling distribution
- Sampling Techniques
- Types of Random variables: Discrete & Continuous
- Probability Distributions
- “Frequestist” Probability: Monte Carlo Simulations, Bayesian probability
- Profitability Analysis
- Time Series Analysis and Forecasting
- Marketing strategy analysis: Demand curve & Pricing
- Value at Risk: Non Parametric (Historical) VaR
- Variance-Covariance, Risk modeling
- Probabilities in action: Calculating an Optimal Bid
- Excel exam
- What is a Database? — Definition, Meaning, Types, Example
- Describing the fundamental building blocks: tables, columns, primary keys, and foreign keys
- Relational Databases and SQL
- Basic Data Types of SQL
- Numeric
- Character
- Boolean
- Datetime
- Learn to write common SQL commands including SELECT and FROM
- Retrieving data with SELECT
- Specifying column expressions
- Sorting the result with ORDER BY - DESC ,ASC Query with EXAMPLE
- Handling NULL values in expressions
- Restricting rows with the WHERE filter AND, OR, IN, NOT IN Query
- Testing for equality or inequality
- Applying wildcard characters — Like, NOT Like, Escape, ( % ), ( _ )
- Avoiding NULL value pitfalls - IS NULL , IS NOT NULL
- LIMIT , OFFSET — Learn with Example
- Introduction to single row functions
- Character Functions
- Numeric Functions
- Conversion Functions
- Date Functions
- Conditional formatting with the CASE expression
- • Utilizing the CASE expression to simulate IF tests
- Date Functions
- Utilizing the CASE expression to simulate IF tests
- Building the Database Schema and SQL Basics
- Building tables with CREATE TABLE
- Modifying table structure with ALTER TABLE
- Adding columns to an existing table
- Removing tables with DROP TABLE
- Protecting data integrity with constraints
- Guaranteeing uniqueness with primary key constraints
- Enforcing integrity with foreign key constraints
- Improving performance with indexes
- Manipulating Data
- Adding table rows with INSERT
- Changing row content with UPDATE
- Removing rows with DELETE
- Learn to write INNER JOINs to combine data from multiple tables
- Learn to write LEFT JOINs and RIGHT JOINs to combine data from multiple tables
- Creating a Cartesian product with CROSS JOIN
- Stacking results with UNION
- Identifying matching rows with INTERSECT
- Testing the existence of rows
- Placing subqueries in the column list
- Creating complex expressions containing subqueries
- Selecting data from a query result set
- Summarizing data using SUM, AVG and COUNT
- Finding the highest/lowest values with MAX and MIN
- Defining the summary level with GROUP BY
- Applying filter conditions with HAVING
- Introduction to Analytic functions
- Syntax for Analytic functions
- the Partition Clause
- Order By Clause
- Row number Functions
- Rank Function
- Dense_rank Function
- Lag Function
- ListAgg Function
- Lead Function
SQL exam
- Introduction
- Downloading Power BI & adjusting settings
- Exploring the Power BI Desktop interface & workflow
- Helpful Power BI resources
- Connecting and Shaping Data with Power BI Desktop
- Connect to data sources
- Types of data connectors in Power BI Desktop
- Change the data source settings
- The Power BI Query editor (aka Power Query)
- Basic table transformations in Power BI
- Working with text tools
- Working with numerical values
- Working with date & time tools
- Shape and transform tables
- User-friendly naming conventions
- Resolving inconsistencies & nulls
- Evaluate and transform column data types
- Append queries
- Merge queries and expand table
- Merge queries with group by, and different types of joins"
- Pivot & Unpivot
- Conditional columns
- Columns from examples
- Transpose
- Data profiling
- Resolve data import errors
- Files from folders
- What is a “Data Model”?
- Principles of data normalization
- Understanding data tables vs. lookup tables
- Creating table relationships in Power BI Desktop
- Design a data model that uses a “Star” schema
- "Snowflake" schemas in Power BI
- Managing & editing table relationships in Power BI Desktop
- Managing active vs. inactive relationships
- Understanding relationship cardinality
- Understanding filter flow
- Two-way filters in Power BI Desktop (USE WITH CAUTION!)
- Hiding fields from the Power BI report view
- Table and column properties
- Common date table (using DAX and Power Query)
- Hierarchies and data granularity
- Role playing dimensions
- Power BI data model best practices
- Intro to Data Analysis Expressions (DAX)
- Intro to DAX calculated columns
- Basic operators IF, BLANK and ISBLANK
- Measures -an introduction, with standard aggregations including COUNTBLANK
- Aggregation of calculations
- Other statistical functions
- Rounding functions
- Division functions - MOD and QUOTIENT SIGN (and use with SWITCH) and ABS
- Text searching
- Text extraction and substitution
- Text conversion
- Other text functions
- ISERROR and LOOKUPVALUE
- Other information functions
- RELATED - Flatten out a parent-child hierarchy
- RELATEDTABLE and COUNTROWS
- ALL, FILTER, CALCULATE, ALLEXCEPT, ALLSELECTED
- Date and time functions, FIRSTDATE, LASTDATE
- Start of... and End of..., Previous... and Next...
- DATESINPERIOD, DATESMTD, DATESQTD, DATESYTD, TOTALMTD, TOTALQTD, TOTALYTD
- Opening Balance and Closing Balance
- Semi-additive measures
- SAMEPERIODLASTYEAR and PARALLELPERIOD
- Other Time Intelligence Functions
- Quick measures
- Exploring the “Report” view in Power BI Desktop
- Table and matrix
- Column charts, line charts and area charts
- Combo charts and treemaps
- Card, multi-row card, and gauge visual
- Pie chart, donut chart and funnel
- Scatter chart, waterfall chart and maps
- Customize and configure visuals
- Custom tool tips
- Configure report page
- Conditional formatting
- Applying slicing and filtering
- Sorting
- Synch slicers
- Using themes
- Bookmarks
- Page navigation
- Edit interactions
- Analyze feature, Identify outliers
- Create groups, bins and clusters
- Analytics pane, Forecast feature
- Logging into Power BI Service and a quick look around
- Power BI terminology
- Datasets and Reports in Power BI Service
- Publish reports and export data
- Create a workplace
- Manage tiles in a dashboard
- Analyze in Excel feature
- Connect to data sources
- Prepare data for analysis
- Customize fields
- Understand dimensions and measures
- Understand discrete and continuous fields
- Understand aggregations
- Create basic charts
- Create and use filters
- Create parameters to enable interactivity
- Create calculated fields
- Create table calculations
- Structure the data
- Map data geographically
- Create dashboards and stories
- Summarize, model, and customize data by using the Analytics feature
Power BI exam
Python basics
- Syntax
- Variables & Data Types (Strings, Numbers)
- Getting Input from Users
- If Statement
- Lists, Tuples, Sets, Dictionaries
- Loops
- Functions, Lambda
- Error handling (Try / Except)
- Built-in packages (random, os, request, math)
- Python for data analysis
- Data frames, reading data from csv, html, json
- Filtering, and sorting
- Adding/removing columns
- Updating Rows and Columns
- Conditional changes
- Join, merge, append
- Indexing
- Aggregation
- Cleaning data
- Casting datatypes
- Working with datetime
- Line plot
- Bar chart
- Pie chart
- Histogram
- Time series
- Subplots
Python exam
Course details
🗓
Schedule
Monday 19:30-21:30
Friday 19:30-21:30
💳
Payment
Monthly
🎓
Certificate
On completion
46 lessons
Frequently asked questions
Each course is labelled beginner, intermediate or advanced. If you are unsure, book a free consultation and we will help you choose.
Flexible payment options are available for most programs. Contact us to discuss the right plan for you.
Certificates
Certificates you can receive
Depending on the course format and results, students can receive one of BDG's certificate types.
- ✓ Verified BDG certificate
- ✓ QR / signature-ready format
- ✓ Armenian & English certificate design
Co-branded
Participation
For students who actively participate in the course learning process.
For active participationCompletion
For students who complete the course requirements and finish the program.
For successful completionExcellence
For students who complete the course with outstanding results and strong performance.
With distinctionHR Drone
A co-branded certificate for selected HR and partner-certified programs.
Co-brandedData Science
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5 months · Starts — Aug 21, 2026
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