Power BI · DAX · Microsoft Fabric · Copilot · Copilot Studio agents · PL-300 · Enrolling now

Power BI & AI Agents

A career-focused, hands-on program: build strong Power Query, data modelling, DAX and report design foundations, then specialise in Microsoft Fabric, Power BI Copilot and AI agents built in Copilot Studio and Fabric — delivering governed, Copilot-ready semantic models and conversational analytics the way Microsoft-stack teams now work.

100K+
alumni community
1,000+
hiring partners
4.8/5
avg class rating
12
partner centres
7
Edify Nuva centres
Where our Power BI alumni work
MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL
Direct answer

What is the Power BI & AI Agents program?

A Power BI specialist turns enterprise data into governed semantic models and reports people trust — and now into Copilot-ready models and AI agents that answer business questions in natural language. Most Power BI courses end at a dashboard. This program ends only when you have shipped a certified semantic model on Fabric, a report suite with row-level security and deployment pipelines, Copilot tuned to answer correctly, and a Copilot Studio or Fabric data agent stakeholders can use in Teams.

The complete delivery chain Twelve links, one owner — end to end.
01CONNECT & MODEL
  • Power Query & Dataflows Gen2
  • Star schema, relationships & grain
  • DAX measures & time intelligence
  • Fabric Lakehouse, Warehouse & Direct Lake
02DESIGN & DELIVER
  • Report design, UX & accessibility
  • Row-level security & workspaces
  • Deployment pipelines & apps
  • Performance tuning & capacities
03AI & GOVERN
  • Copilot-ready semantic models & linguistic schema
  • Fabric data agents & Copilot Studio agents
  • Purview, certification & endorsement
  • Adoption, monitoring & PL-300
Power BI & Fabric in 2026

Power BI became the AI front door to Fabric. Modellers became the people who make Copilot right.

Power BI CopilotAI in the product
Copilot writes DAX, builds report pages, summarises visuals and answers questions in the standalone Copilot experience — but only as well as the semantic model, descriptions and linguistic schema beneath it.
Microsoft Fabric & OneLakePlatform layer
Power BI now sits on Fabric — Lakehouse, Warehouse, Dataflows Gen2, Real-Time Intelligence and Direct Lake mode. Capacities and OneLake replaced the old Premium and dataset model.
Fabric data agents & Copilot StudioNew '26
Data agents over Lakehouse, Warehouse and semantic models, and Copilot Studio agents published to Teams and Microsoft 365 Copilot — conversational analytics that Power BI specialists now build and govern.
Copilot-ready semantic modelsTrust layer
Descriptions, synonyms, verified answers, the linguistic schema and the Prep data for AI settings decide whether Copilot answers correctly. Model quality became the core Power BI skill.
Governance with Purview & endorsementGovernance layer
Certified and promoted semantic models, sensitivity labels, Purview lineage and tenant settings for Copilot — what enterprises audit before AI answers reach executives.
Open standards & interoperabilityEcosystem
TMDL, Git integration, Power BI Projects, Tabular Editor, DAX Studio and MCP connections to Fabric — Power BI development now looks like software development.

What this means for your career: Power BI roles now ask for Fabric, Copilot and agent skills alongside DAX and modelling — the differentiator is a certified, Copilot-ready semantic model on Fabric with a working data agent and governance evidence, not a PL-300 badge alone.

Who should join

Built for people moving into Microsoft-stack analytics and AI.

Excel & MIS reporting professionals Business, finance & operations analysts Graduates targeting BI & analytics roles Tableau, Qlik or SAP BO developers moving to Power BI Data analysts adding Fabric & Copilot IT staff supporting Microsoft 365 & Azure

Prior experience: none required — Power BI, DAX and SQL are taught from scratch. The program builds modelling and report foundations before Fabric, Copilot and AI agents.

What you will be able to do

Model the data — and make Copilot answer correctly.

Shape data with Power QueryConnectors, transformations, query folding, parameters and Dataflows Gen2.
Model and write DAXStar schemas, relationships, CALCULATE, filter context, time intelligence and performance tuning.
Design reports people useVisual design, interactions, bookmarks, accessibility, mobile and paginated reports.
Deploy and govern on FabricWorkspaces, RLS, deployment pipelines, Git integration, capacities, Purview and endorsement.
Make Copilot trustworthyCopilot-ready models, linguistic schema, verified answers and evaluation of Copilot output.
Build AI agentsFabric data agents and Copilot Studio agents over semantic models, published to Teams with guardrails.
Course curriculum

Twelve sections. 55 modules. Power Query → Modelling → DAX → Design → Fabric → Copilot → Agents.

01

Fundamentals of BI, Power BI & Fabric

Business intelligence, the Power BI ecosystem and where it sits inside Microsoft Fabric in 2026.
4 MODULES
SECTION 1
BI, analytics and the data-to-decision cycle
Power BI, Tableau and Qlik compared
Roles — BI developer, analyst, analytics engineer
Career pathways and Microsoft certifications
Desktop, Service, Mobile, Report Builder and Report Server
Licensing — Free, Pro, Premium Per User, Fabric capacities
Workspaces, apps and tenants
Release cadence and feature summaries
OneLake and the unified lakehouse
Fabric workloads — Data Factory, Engineering, Warehouse, Real-Time Intelligence, Power BI
Capacities and SKUs
Where Power BI fits in Fabric
Installing Power BI Desktop and enabling preview features
Fabric trial and workspace setup
Copilot, ChatGPT and Claude as learning and DAX assistants
Verifying AI-generated DAX
02

Data Sources & Power Query

Connect to anything and shape it into analysis-ready tables.
5 MODULES
SECTION 2
Excel, CSV, SharePoint and folders
SQL Server, PostgreSQL and cloud databases
Web, APIs and OData
Fabric Lakehouse and Warehouse connectors
Column operations, types and data cleaning
Merge, append and pivot / unpivot
Grouping and conditional columns
Applied steps and the Advanced Editor
M syntax, functions and parameters
Custom functions and error handling
Query folding and performance
Reusable query templates
Dataflows Gen2 in Fabric
Staging and destinations
Shared transformations across reports
Refresh and incremental refresh
Import vs DirectQuery vs composite models
Direct Lake mode on OneLake
Choosing a storage mode
Performance implications
03

Data Modelling

The star schema — the foundation of fast reports and correct Copilot answers.
5 MODULES
SECTION 3
Facts, dimensions and grain
Star vs normalised schemas
Surrogate keys and date tables
Common modelling mistakes
Cardinality, direction and active relationships
Role-playing dimensions
Many-to-many and bridge tables
Model view and layouts
Calculated columns vs measures
Calculated tables and date tables
Hierarchies and drill paths
Field parameters
VertiPaq and columnar storage
Reducing model size
Aggregations and incremental refresh
DAX Studio and Tabular Editor
Descriptions, synonyms and the linguistic schema
Prep data for AI and verified answers
Hiding, folders and naming for AI
Testing Copilot against the model
04

DAX

From first measure to advanced calculations that run fast.
6 MODULES
SECTION 4
Measures, syntax and data types
Aggregation functions
Implicit vs explicit measures
Formatting and measure tables
Row context vs filter context
CALCULATE and CALCULATETABLE
FILTER, ALL, ALLSELECTED and REMOVEFILTERS
Context transition
Date tables and marking
YTD, MTD, QTD and prior period
Rolling averages and moving windows
Fiscal calendars
SUMX, AVERAGEX and RANKX
Variables and readability
Semi-additive measures
Dynamic segmentation and what-if
Performance Analyzer and DAX Studio
Storage engine vs formula engine
Common anti-patterns
Optimising slow measures
Generating measures with Copilot
Explaining and documenting DAX with AI
Validating generated logic
Prompt patterns for DAX
05

Report Design & Visualisation

Reports that communicate — fast, accessible and on brand.
5 MODULES
SECTION 5
Core visuals and when to use them
Custom visuals and AppSource
Conditional formatting
Small multiples and decomposition tree
Slicers, filters and sync
Bookmarks, buttons and page navigation
Drill-through and tooltips
Report themes and layouts
Visual hierarchy and layout grids
Colour, contrast and accessibility
Mobile layouts
Design reviews
Q&A visual and synonyms
Key influencers and anomaly detection
Smart narrative and Copilot summaries
Forecasting in line charts
When paginated reports fit
Report Builder basics
Parameters and exports
Publishing to the Service
06

Power BI Service, Security & Deployment

Publish, secure and run reports at enterprise scale.
5 MODULES
SECTION 6
Workspace roles and design
Apps and audiences
Sharing, subscriptions and alerts
Usage metrics
Static and dynamic RLS
Testing roles
Object-level security
Security with Direct Lake and composite models
On-premises data gateway
Scheduled and incremental refresh
Refresh failures and monitoring
Large semantic model format
Deployment pipelines — dev, test, prod
Power BI Projects and TMDL
Git integration in Fabric
Version control and code review for BI
Capacity metrics app
Optimising reports for capacities
Query caching and scale-out
Cost management
07

SQL for BI Developers

Enough SQL to shape data before it reaches the model.
3 MODULES
SECTION 7
SELECT, WHERE, JOIN and GROUP BY
Subqueries and CTEs
Data types and NULLs
Views for BI
Window functions
Date logic and period comparisons
Fabric Warehouse T-SQL
SQL analytics endpoint on Lakehouse
Views and staging for star schemas
Pushing transformations to the source
Query folding to SQL
Text-to-SQL with Copilot and validation
08

Microsoft Fabric for Power BI Professionals

Work across the Fabric workloads a Power BI developer now touches.
5 MODULES
SECTION 8
OneLake architecture and shortcuts
Creating a Lakehouse and loading data
Delta tables and the SQL endpoint
Direct Lake semantic models
Warehouse creation and T-SQL
Data pipelines and Dataflows Gen2
Copy activities and scheduling
Medallion patterns for BI
Spark notebooks for BI developers
Eventstreams and KQL basics
Real-time dashboards
Activator alerts
Tenant settings and admin portal
Capacities, SKUs and monitoring
Domains and workspace governance
Cost optimisation
Copilot in Data Factory, notebooks and Warehouse
Copilot in Power BI in Fabric
Enabling and governing Copilot
Verifying generated artefacts
09

Power BI Copilot & Conversational Analytics

Make Copilot answer correctly — and measure it.
4 MODULES
SECTION 9
Copilot in Desktop and Service
Standalone Copilot experience
Report creation and summaries
Licensing and tenant prerequisites
Prep data for AI settings
Linguistic schema and synonyms
Verified answers
Model quality checklist
Testing Copilot with golden questions
Handling wrong answers
Usage monitoring and adoption
Governance and tenant controls
Generating report pages and DAX
Narratives and measure descriptions
Copilot for Power Query
Productivity patterns
10

AI Agents — Fabric Data Agents, Copilot Studio & MCP

Build the agents that let stakeholders ask the data directly.
6 MODULES
SECTION 10
Copilots vs agents
How agents use semantic models and SQL
Grounding, guardrails and evaluation
Where BI developers build vs configure
Creating a data agent over Lakehouse, Warehouse and semantic models
Instructions, example queries and scope
Testing and publishing
Consuming from Copilot Studio
Building agents in Copilot Studio
Knowledge sources, topics and actions
Connecting to Fabric data agents and Power BI
Publishing to Teams and Microsoft 365 Copilot
Flows triggered from Power BI and agents
Data alerts and actions
Approvals and notifications
Automation governance
Model Context Protocol basics
Fabric and Power BI MCP servers
Claude and ChatGPT querying semantic models
Security and permissions
Purview, sensitivity labels and agent access
Evaluating agent accuracy with golden questions
Responsible AI and the EU AI Act
Adoption and change management
11

Governance, Data Culture & Analytics Storytelling

Run Power BI as a governed platform — and get it used.
3 MODULES
SECTION 11
Certified and promoted models
Sensitivity labels and DLP
Purview lineage and catalog
Data loss prevention
Power BI adoption roadmap
Centre of Excellence and champions
Self-service vs managed BI
Training and support models
Insight narratives and executive summaries
Presenting dashboards to leadership
Metric definitions and KPI ownership
Handling questions and pushback
12

Capstone, PL-300 & Career

A certified Fabric-based BI platform with Copilot and an agent — and Microsoft certification.
4 MODULES
SECTION 12
Lakehouse and Direct Lake semantic model
DAX measures, RLS and deployment pipelines
Copilot-ready model with verified answers
Public verification URL
Fabric data agent over the semantic model
Copilot Studio agent published to Teams
Golden-question evaluation and guardrails
Demo and write-up
PL-300 Power BI Data Analyst objectives
DP-600 Fabric Analytics Engineer objectives
Practice exams
Study plan
Portfolio of reports, models and agents
Resume rewrite around business impact
Power BI interview practice — DAX, modelling, scenarios
Warm introductions to hiring partners
Tools you'll master

32+ Power BI & AI tools, one production project.

PBI
Power BI
DAX
DAX
PQ
Power Query
Svc
Power BI Service
Fab
Microsoft Fabric
OL
OneLake
SyN
Azure Synapse
ADF
Azure Data Factory
DLg
Dataflows Gen2
TSQ
T-SQL
KQL
KQL
Py
Python
R
R
Ex
Excel
OAI
Azure OpenAI
CP
Copilot
LC
LangChain
LG
LangGraph
MCP
MCP
Tb
Tableau
GDS
Looker Studio
Snw
Snowflake
DBX
Databricks
BL
Delta Lake
ABR
Azure Data Bricks
Pwr
Power Automate
PA
Power Apps
G
Git
GH
GitHub
aws
AWS
Az
Azure
C
Cursor AI
Real-time projects

You don't watch videos. You ship software.

Three portfolio projects and a partner capstone, each threaded through the entire curriculum — Power Query, modelling, DAX, Fabric, Copilot and agents all land in real deliverables.

Hero project

Sales & Finance executive dashboard on Fabric

Build an end-to-end executive analytics platform — Fabric lakehouse ingestion, a Direct Lake semantic model, and a Copilot for Power BI experience that drafts variance narratives and answers natural-language questions live on the dashboard.

01Live Fabric workspace with bronze/silver/gold lakehouse, Dataflows Gen2 ingestion, and Direct Lake semantic model.
02Composite DAX model with row-level security, calculation groups, and field parameters wired to a Power BI Service workspace.
03Copilot for Power BI drafting variance narratives, suggesting visuals, and generating natural-language Q&A on the fly.
04Refresh + alert pipeline that flags revenue/forecast gaps and writes to Teams + email with a Fabric Activator trigger.
Outcome: ~60% faster monthly close
Report build time: −45%
Reviewer: Microsoft MVP panel
Power BIFabricDAXCopilotDirect Lake
Enterprise

Finance forecasting + RLS workspace

Multi-perspective DAX model with row-level security, scenario calculation groups, what-if parameters, and a Copilot agent that drafts FP&A commentary on every refresh.

DAXRLSCalc GroupsCopilot
Real-time

Real-time ops streaming dashboard

Stream KQL events into a Power BI real-time dashboard, classify anomalies with Fabric ML, and auto-create alerts with AI-drafted root-cause summaries.

KQLReal-Time IntelligenceFabric MLActivator
Project

Your AI Power BI agent in a controlled project environment.

Pick a real partner workflow. Deploy a production Power BI + Fabric solution — Direct Lake semantic model, Copilot agent, Activator alerts — that handles board-level reporting and accelerates decisions.

Download the real world project
Full scope, sample deployment contexts, project milestones, and grading rubric — PDF, 14 pages.
Production-style capstoneCareer support included
Your instructor

Taught by engineers who shipped agentic AI to production.

MK
Manikanta Kona
Founder, Edify Nuva · Principal Power BI Architect
Power BI · DAX · Microsoft Fabric · Copilot · Sales / Finance / Operations / Marketing analytics
"Power BI at enterprise scale is where AI earns its keep — Copilot plugged into board-level dashboards, Fabric orchestrating Sales, Finance, Operations, and Marketing analytics as one semantic fabric. That's the bar I teach to, every class."
15 yrs
POWER BI
2,400+
LEARNERS
4.8 /5
RATING

Manikanta is the founder of Edify Nuva and brings 15 years of enterprise data & analytics architecture from AT&T, Salesforce, Cox Communications, and Broadcom — where he led Power BI, Fabric, and data-warehouse rollouts for Fortune-500 banks, telcos, and insurers. Most recently he architected production Copilot for Power BI + Microsoft Fabric deployments that replaced static monthly decks with live, agent-assisted decision dashboards.

His classes get you two things other programs don't give you: a founding architect who's shipped enterprise Power BI & AI Agents from inside the Fortune 500, and a curriculum rewritten every release — so when hiring managers ask about Direct Lake semantic models, calculation groups, RLS, or Copilot governance, you've already built it. M.S. in Engineering, Purdue University.

RK
Ravi Krishna
Chief Technologist, Edify Nuva · Data & Fabric Lead
Power BI · DAX · Microsoft Fabric · Copilot · OneLake · Azure Synapse · KQL
"Power BI stops being a chart tool and starts being the nervous system of the enterprise the moment Fabric is wired in — OneLake feeding a Direct Lake semantic model you can trust, DAX that holds up under RLS, and Copilot drafting the narrative before the meeting starts. That's what I teach."
10 yrs
DATA & BI
1,800+
LEARNERS
4.8 /5
RATING

Ravi is Chief Technologist at Edify Nuva, where he leads the Data & Fabric practice. After 8 years building and running production data platforms on Azure Synapse, Databricks, and Power BI, he stepped into the Chief Technologist seat to wire Microsoft Fabric, Copilot, and OneLake into the way analytics teams actually work — semantic models that survive a re-org, DAX that scales beyond a billion rows, and governance so finance leadership trusts the numbers.

His Fabric and DAX modules are built from real production rebuilds, not slide decks. Expect to leave with working Direct Lake semantic models, calculation groups + field parameters, row-level security patterns, and a Copilot agent you can actually demo. Ten years at Edify Nuva, eight of them shipping data & BI in production — Hyderabad-based, hands-on, and known for the unglamorous parts of analytics that everyone else skips.

HIRING PARTNERS · INDUSTRY VOICES

What Power BI employers say about Edify Nuva grads.

Real feedback from talent leaders at Microsoft Fabric partners and the firms hiring our Power BI & AI Agents Copilot graduates.

Microsoft logo

Edify Nuva grads ramp 40% faster on Fabric and Copilot for Power BI projects than typical hires. Best Power BI training pipeline in India.

Aakash Mehta

Aakash Mehta, Partner Programme Lead, Microsoft

Deloitte logo

We've onboarded 80+ Edify Nuva alumni in 18 months. Lowest ramp time we've seen for Power BI plus Microsoft Fabric practices.

Anita Sharma

Anita Sharma, Senior Manager, Deloitte

Mphasis logo

The Power BI programme is comprehensive — DAX, Fabric, plus Copilot governance. Grads come pre-trained for enterprise analytics teams.

Rahul Bhatt

Rahul Bhatt, Solutions Lead, Mphasis

TCS logo

Their DAX + Fabric track produces engineers who write production-grade semantic models on day one. Genuinely rare.

Deepak Pillai

Deepak Pillai, Senior Architect, TCS

Accenture logo

What sets Edify Nuva apart is the Copilot for Power BI layer baked into the Fabric track. Our enterprise clients ask for exactly this profile.

Suresh Menon

Suresh Menon, Practice Lead, Accenture

Infosys logo

Their PL-300 + DP-600 prep is rigorous, and the project deployment on a real Fabric tenant is what closes interviews for us.

Vikram Iyer

Vikram Iyer, Director, Infosys

Wipro logo

Edify Nuva's Power BI grads cut report build time in half in the first 90 days. Our internal metrics back this up clearly.

Lakshmi Nair

Lakshmi Nair, VP Engineering, Wipro

Cognizant logo

Best Power BI & AI Agents Copilot pipeline we've sourced from in India. Their projects are production work on Fabric, not toy dashboards.

Karthik Subramanian

Karthik Subramanian, Engineering Director, Cognizant

Capgemini logo

Strong DAX and semantic model foundation. Their Power BI grads need almost zero ramp time on enterprise Fabric engagements with us.

Arun Joshi

Arun Joshi, Practice Director, Capgemini

IBM logo

We've placed 40+ Edify Nuva alumni across our Power BI and watsonx-on-Fabric teams. Strong DAX fundamentals, sharp on the Copilot stack.

Sanjay Verma

Sanjay Verma, Talent Director, IBM

LTIMindtree logo

Direct Lake + Real-Time Intelligence is exactly the talent gap we've been struggling to close. Edify Nuva is filling it for us reliably.

Anjali Desai

Anjali Desai, Practice Head, LTIMindtree

Tech Mahindra logo

Their Power BI track delivers consultants who navigate DAX, Power Query, and Copilot governance on customer engagements unsupervised.

Ramesh Iyer

Ramesh Iyer, Senior Manager, Tech Mahindra

Cyient logo

Hired 25+ Edify Nuva graduates for our Power BI practice. Strong DAX, strong Fabric depth, sharp on the Copilot layer.

Geetha Pillai

Geetha Pillai, Talent Acquisition Lead, Cyient

Microsoft logo

Edify Nuva grads who blend Power BI with Azure OpenAI and Copilot land production-ready on day one. Rare combination, well-trained.

Priya Reddy

Priya Reddy, Talent Lead, Microsoft

03Program certifications

An Agent‑Ready credential, not a participation trophy.

Edify Nuva · Institute Certificate
Agent‑Ready Power BI Engineer
Presented to
Spandana Bala
For the successful design, build, and production deployment of a Direct Lake semantic model and Copilot for Power BI agent on Microsoft Fabric, evaluated against the 2026 Agent‑Ready rubric and PL‑300 / DP‑600 competencies.
Manikanta Kona
CEO · Edify Nuva
AGENT
READY
2026
01
Industry‑recognized
Co‑branded with the Microsoft Fabric partner ecosystem and mapped to PL‑300 and DP‑600 — names that hiring managers already scan for on resumes.
02
Project artifact included
Every certificate carries your project project name, the partner org, and a link to the deployed Power BI + Fabric Copilot artifact — proof, not a promise.
03
Enhanced skill validation
Graded against the 2026 Agent‑Ready rubric: DAX modelling, Fabric pipeline build, Copilot deployment, governance and monitoring. No pass/fail — a level 1‑5 band.
04
Verifiable on a public URL
Each credential has a public verification page recruiters can check in 10 seconds — no PDF back‑and‑forth.
Job roles

Roles this program prepares you for.

Power BI Developer Build semantic models, DAX and report suites for the business.
Business Intelligence Analyst Answer business questions with Power BI and SQL.
Fabric Analytics Engineer Lakehouse, Warehouse and Direct Lake models on Microsoft Fabric.
Power BI Administrator Tenant settings, capacities, governance and Copilot enablement.
Data Modeller / Semantic Layer Developer Own certified, Copilot-ready semantic models.
Conversational Analytics / AI Agent Developer Fabric data agents and Copilot Studio agents over BI data.
Reporting & MIS Analyst (upgraded) Move from Excel to governed Power BI and automation.
Analytics Consultant (Microsoft partner) Deliver Power BI and Fabric implementations for clients.
Data Visualisation Specialist Report design, UX and storytelling.
BI Architect (career path) Grow toward designing enterprise analytics platforms.

What employers should see in your portfolio: that you can take enterprise data to a governed, AI-ready analytics platform — shape it in Power Query and Fabric, model it as a certified star schema with fast DAX, design reports people use, secure and deploy them, make Copilot answer correctly, and ship a data agent stakeholders can ask in Teams.

04Job placement support

Your first Power BI offer isn't a lottery ticket. It's a built process.

GitHub, LinkedIn, resume — and most importantly, warm intros into Microsoft Fabric partners. Our placement team works your search like an account, not a helpdesk.
01 / GITHUB PROFILE

A portfolio, not a graveyard.

Guidance on building a GitHub that showcases your PBIX files, Direct Lake semantic models, Fabric workspace artifacts, DAX patterns, and a working Copilot agent — reviewed 1:1, not via template.

02 / RESUME PREP

Rewrite, don't proofread.

A one-page resume rebuilt around the Power BI stacks you implemented (DAX, Fabric, Direct Lake), the Copilot agent you deployed, and the business outcome. Reviewed by engineers who've read 10,000+ resumes.

03 / LINKEDIN + INTROS

Where most opportunities actually live.

Profile tuning plus direct warm introductions into the Microsoft Fabric partner network — Deloitte, Accenture, Cognizant, Capgemini, EY, KPMG, Microsoft, Wipro, Infosys, TCS. You leave with recruiter contacts, not a generic "good luck."

Power BI alumni

Hundreds of Power BI careers launched — here are eight.

SB
Spandana Bala
Power BI Developer
Hyderabad · India
Now at · Infosys
NV
Naveen Vedala
Fabric Data Engineer
Hyderabad · India
Now at · TCS
TA
Tejashwini Addla
BI Analytics Lead
Hyderabad · India
Now at · Deloitte
TD
Tharunesh Dillikar
DAX Specialist
Seattle · United States
Now at · Microsoft
MM
Mujahed Mohammed
Copilot Solutions Engineer
Hyderabad · India
Now at · Accenture
BK
Bhargav Kumar Murala
BI Consultant
Hyderabad · India
Now at · Capgemini
SL
Sai Manasa Leburi
Real-Time Intelligence Lead
New York · United States
Now at · EY
RD
Rahul Dhamma
Data Visualization Engineer
Hyderabad · India
Now at · Cognizant
Our locations

Come chat with us — over coffee, or over Zoom.

One flagship campus in Hyderabad, plus online Power BI classes running on Indian and US timezones.

Flagship campus
Hyderabad
2nd Floor, Hitech City Road · Above Domino's · Opp. Cyber Towers, Jai Hind Enclave · Hyderabad, Telangana
Call
+91 8142998866
US desk
+1 256 388 7766
Hours
Mon–Sun · 7 AM–9 PM
Online class
Global
Weekend and evening Power BI classes running on IST and PST. Every online class ships the same three production projects and Direct Lake + Copilot project as the on‑campus track.
Timezones
IST & PST
Format
Live + 1:1 mentorship
Admissions
ENROLLING NOW
FAQ

Questions we actually get — answered honestly.

Straight answers on prerequisites, the platform, certifications, and placement. If something's missing, book a 20-minute advisor call — no slides, no pitch.

Do I need an analytics or SQL background?+
No. Roughly 40% of every class comes from non-analytics streams — mechanical, electrical, BCom, BBA — and zero Power BI exposure is assumed. The opening modules cover Excel modelling, basic SQL, and the Power Query / DAX foundations from scratch. What you do need is consistency and regular practice.
Do I get a real Power BI / Fabric tenant to build on?+
Yes. Every learner provisions a free Microsoft 365 developer tenant with a Fabric trial workspace from the start and keeps it for the full program. Every lab, project, and the project are built on your own live workspace — not a sandbox simulator — so the artifacts you ship are demonstrable to recruiters.
Which tools and AI capabilities will I actually build with?+
Core: Power BI Desktop, DAX, Power Query, Power BI Service, Microsoft Fabric, OneLake, Dataflows Gen2, Direct Lake. AI track: Copilot for Power BI (narratives, Q&A, visual generation), Azure OpenAI for custom agents, Fabric Real-Time Intelligence for streaming, and Activator for AI-driven alerting.
Will I be ready for PL-300 and DP-600 certifications?+
Yes. The curriculum is mapped to PL-300 (Power BI Data Analyst Associate) and DP-600 (Fabric Analytics Engineer Associate); enterprise-track learners also prep for DP-500. We run two full mock exams and reimburse the voucher fee on first-attempt pass.
How is the learning workload structured?+
The program combines live mentor-led classes, guided labs, project work, and optional support sessions. An advisor can explain the current class format before enrolment.
Is placement support really 1:1, and which companies hire?+
Yes. Career support includes portfolio and profile preparation, interview practice, and role-fit introductions where available. Edify Nuva does not guarantee an interview, offer, salary, employer, location, or timeline.
Online, weekend, or on-campus?+
All three. On-campus at the Hyderabad flagship, live online (IST and PST classes), and a weekend track for working professionals. Every format ships the same three projects and the same project — only the schedule changes.
What if I fall behind, or can't continue mid-class?+
Freeze your seat for up to 90 days and rejoin the next class — no extra fee. TAs run catch-up sessions every Saturday for learners needing additional support, and recordings of every live session are available for the lifetime of your account.

Still have a question? Talk to an advisor — no slides, no pitch.

One million AI‑native professionals by 2027.
Let's put you in that number.

Book a 20‑minute advisor call. We'll map your current role to the right program, talk honestly about timelines, and walk you through a real class's project.

Get Skilled

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