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Data Science
·Offline
Power BI Full Course
Practical course designed to help you build relevant skills and take the next step in your career.
What you'll gain
- ✓ Connecting and importing data
- ✓ Data transformation and modeling
- ✓ Data visualization and reporting
- ✓ Mastery of data analysis techniques
✓ Free consultation · Certificate on completion · Practical learning
Duration
2 months
Format
Offline
Level
Advanced
Starts
Sep 26, 2026
Certificate
On completion
Lessons
16 lessons
Schedule
- Wednesday · 19:00–21:00
- Saturday · 11:00–13:00
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 is this course for
-
✓
Beginners
Anyone interested in data analysis, visualization, and business intelligence.
-
✓
Specialists in the field
For Business Analysts, Data Analysts, Data Scientists, Managers, Financial Analysts, and anyone for whom quick decision-making based on data analysis is important.
What you will learn
- ✓Connecting and importing data
- ✓Data transformation and modeling
- ✓Data visualization and reporting
- ✓Mastery of data analysis techniques
- ✓Share and collaborate on real-time data and reporting
Program
- 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
- Preparing the data
- Shape and transform tables
- User-friendly naming conventions
- Resolving inconsistencies & nulls
- Evaluate and transform column data types
- Append quearies
- 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
- Data loading with parameters
- Preparing the data
- Shape and transform tables
- User-friendly naming conventions
- Resolving inconsistencies & nulls
- Evaluate and transform column data types
- Append quearies
- 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
- Data loading with parameters
- Python for Data Analytics & Power BI Integration
- Introduction to Python
- Setting Up Anaconda: Your Python Environment
- Introduction to String Functions
- Lists and For Loops: Harnessing the Power of Iteration
- Mastering User-Defined Functions in Python
- Intro to Pandas, NumPy, Matplotlib and Seaborn libraries
- Mastering Dictionaries and Dataframes in Python
- Building Cleaning Functions for Data Preprocessing
- Visualizing Cleaned Data: Unveiling Patterns and Insights
- Exploring Three Ways to Harness Python Scripting in Power BI
- Using Python Scripts as Data Sources in Power BI
- Data Transformation with Python inside Power BI
- Using Python instead of Power Query for complex transformations
- Comparing Power Query vs Python approaches
- Python for Data Analytics & Power BI Integration
- Introduction to Python
- Setting Up Anaconda: Your Python Environment
- Introduction to String Functions
- Lists and For Loops: Harnessing the Power of Iteration
- Mastering User-Defined Functions in Python
- Intro to Pandas, NumPy, Matplotlib and Seaborn libraries
- Mastering Dictionaries and Dataframes in Python
- Building Cleaning Functions for Data Preprocessing
- Visualizing Cleaned Data: Unveiling Patterns and Insights
- Exploring Three Ways to Harness Python Scripting in Power BI
- Using Python Scripts as Data Sources in Power BI
- Data Transformation with Python inside Power BI
- Using Python instead of Power Query for complex transformations
- Comparing Power Query vs Python approaches
- How to use SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY in SQL Server
- INSERT new data, UPDATE and DELETE existing data, and export data INTO a new table
- Creating Views and Procedures
- Indexes in SQL
- Using SQL Server as a Data Source in Power BI
- Creating table relationships & data model in Power BI
- 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
- How to use SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY in SQL Server
- INSERT new data, UPDATE and DELETE existing data, and export data INTO a new table
- Creating Views and Procedures
- Indexes in SQL
- Using SQL Server as a Data Source in Power BI
- Creating table relationships & data model in Power BI
- 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
• AND, OR and NOT
• SWITCH
• 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
• COUNT functions (COUNTA, DISTINCTCOUNT, COUNTROWS), exponential function
• Text searching
• Text extraction and substitution
• Text conversion
• Other text functions
- Information, Iterator, Filter & Value and Time Intelligence DAX functions
- ISERROR and LOOKUPVALUE
- Other information functions
- SUMX, AVERAGEX, MAXX/MINX, RANKX, COUNTX
- RELATED - Flatten out a parent-child hierarchy
- Context
- 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
- Information, Iterator, Filter & Value and Time Intelligence DAX functions
- ISERROR and LOOKUPVALUE
- Other information functions
- SUMX, AVERAGEX, MAXX/MINX, RANKX, COUNTX
- RELATED - Flatten out a parent-child hierarchy
- Context
- 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
- Visualize and analyze the data with Power BI
- Exploring the “Report” view in Power BI Desktop
- Table and matrix
- Column charts, line charts and area charts
- Combo charts and treemaps
- Card and gauge visual
- Pie chart, donut chart and funnel
- Scatter chart, waterfall chart and maps
- Customize and configure visuals
- Custom tooltips
- Configure report page
- Conditional formatting
- Applying slicing and filtering
- Sorting
- Synch slicers
- Using themes
- Drillthroughs and drill downs
- Bookmarks
- Page navigation
- Edit interactions
- Analytics pane
- Analyze feature, Identify outliers
- Create groups, bins and clusters
- Create reference lines by using Analytics pane
- Decomposition tree visual
- Custom Visuals
- Python Visuals in Power BI
- Creating custom visuals using Matplotlib & Seaborn
- Limitations and best practices of Python visuals
- When to use Python visuals vs native Power BI visuals
- Visualize and analyze the data with Power BI
- Exploring the “Report” view in Power BI Desktop
- Table and matrix
- Column charts, line charts and area charts
- Combo charts and treemaps
- Card and gauge visual
- Pie chart, donut chart and funnel
- Scatter chart, waterfall chart and maps
- Customize and configure visuals
- Custom tooltips
- Configure report page
- Conditional formatting
- Applying slicing and filtering
- Sorting
- Synch slicers
- Using themes
- Drillthroughs and drill downs
- Bookmarks
- Page navigation
- Edit interactions
- Analytics pane
- Analyze feature, Identify outliers
- Create groups, bins and clusters
- Create reference lines by using Analytics pane
- Decomposition tree visual
- Custom Visuals
- Python Visuals in Power BI
- Creating custom visuals using Matplotlib & Seaborn
- Limitations and best practices of Python visuals
- When to use Python visuals vs native Power BI visuals
- AI and optimization tools in Power BI
- Anomaly detection
- Forecast
- What-If Parameters & Field Parameters for Interactive Reporting
- Smart narratives
- Q&A visuals
- Key Influencers
- The optimize ribbon
- Pausing visuals
- Applying all slicers
- Performance analyzer
- Tabular Model Definition Language (TMDL) & AI for Power BI Model Documentation
- Introduction to DAX Studio
- New Power BI features and updates
- Calculation Groups in Power BI (Time Intelligence, Dynamic Measures, Scenario Analysis)
- DAX query view
- Button Slicer
- List Slicer
- Visual calculations
- Model Metadata Exploration (DAX INFO.VIEW functions)
- Hands-on Projects in Power BI
- Bank Customers Analytics
- Data Storytelling in Power BI
- Sentiment Analysis using AI & Custom Visuals
Ready to join this course?
Secure your place and take the next step in your professional growth.
Your trainer
Hayk Ghalechyan
Head of Data
Hayk Ghalechyan has 12+ years of experience in data analysis in various fields. He has published 8 scientific articles in the fields of economics and management. At BDG, he conduct...
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.
We mostly hold trainings with a Project Based Learning approach. Thanks to this approach, the students gain practical knowledge and develop their proficiency in the most efficient way.
After each training the students pass exams. Thus, both students and trainers have the opportunity to clearly assess the effectiveness of the training. Based on the results of the exams the students get certificates.
Upon completion of the training we give certificates to our students. Moreover, those whose performance is above 80% receive certificates of excellence.
We have developed a partner network that includes current best employers. In cooperation with them we do our best to assist our students in finding jobs. This network also helps us to organise internships for our students after the trainings.
Payment for the courses is made after the first lesson until the second lesson, in cash or by transfer. Payment for each stage is made for a fixed amount of 8 lessons.
Our courses are held in 2 main formats: online and offline. We believe that maintaining the format is very important for the effectiveness of the course.
BDG classrooms are technically equipped, and if necessary, we also provide students with laptops.
There is a break during each course, during which you can have a coffee and tea break.
HR consulting is carried out with our Career Development Specialist. With him, you can discuss your CVs, make corrections and finalize them, ready to apply for jobs.
All course materials, including recordings, books provided by trainers and other educational materials, are constantly available to our students during the course.
Individual courses are not currently designed, based on market needs and demands. During group courses, participants are also actively involved in teamwork, develop their communication skills, and learn to work in a team.
There is no age limit as such, as we value the spread of education to all age groups. It is especially important for us that people who already have experience and knowledge and want to acquire a new profession also go into a new educational direction.
Admission to each course is carried out through an interview or a test, or both at the same time. The choice of admission method depends on the requirements and specifics of the course.
We provide technical support to all our students related to the operational work of computers, as well as technical issues. The support is provided by our employee within the framework of the course.
Our team is in constant contact with students to provide the information you need, if necessary.
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
Ready to start Power BI Full Course?
Book a free consultation and reserve your place in the next cohort.
79,000 ֏ / month
2 months · Starts — Sep 26, 2026
27% booked
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