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Data Analytics With Gen Ai
Intermediate
Data Analytics With Gen Ai
Mr. Savan Rai
Founder & CEO (Python With Gen AI)
★★★★★ (45)
Looking for the best Data Analytics course in Lucknow? This 8-month, industry-oriented program is designed for B.Tech CS/IT, BCA, MCA, and Diploma graduates, taking you from your existing programming/DBMS foundation to a job-ready Data Analyst.
Learn Python, SQL, Excel, Power BI, Tableau, Statistics, Predictive Analytics, and Cloud Analytics tools (BigQuery, AWS/Azure) — the same skills companies look for in real Data Analyst and Business Analyst job postings.
Key highlights:
- 8 portfolio-ready projects plus a real-world capstone
- Weekly interview and case-study preparation
- Hands-on Power BI, Tableau & Predictive Analytics training
- Dedicated placement support — resume, mock interviews, portfolio building
- Beginner-friendly, Hindi/English (Hinglish) instruction
Join Piedocx Technologies' Data Analytics course in Lucknow and become a certified Data Analyst with real project experience and placement support.
What You'll Learn
Python for Data Analytics
NumPy & Pandas
Exploratory Data Analysis (EDA)
SQL Fundamentals & Advanced Queries
Window Functions & CTEs
Database Design & Data Modeling
Statistics & Hypothesis Testing
Excel for Data Analysis
Power Query & Advanced Excel
Data Visualization (Matplotlib, Seaborn, Plotly)
Power BI Fundamentals
Power BI Advanced Dashboards & DAX
Tableau Fundamentals
Data Storytelling & Presentation
Marketing & Product Analytics
Financial & Business Analytics
Predictive Analytics
Time Series Forecasting
Customer Segmentation & Clustering
A/B Testing & Experimentation
Data Warehousing Concepts
Cloud Analytics (BigQuery, AWS/Azure)
Automation & Workflow Tools
Git & Version Control for Data Projects
Capstone Project & Placement Preparation
Course Curriculum
MONTH 1 — PYTHON FOR DATA ANALYTICS
Week 1: Python Refresher for Analytics
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• Quick recap — control flow, functions, data structures
• Jupyter/Google Colab environment setup
• File handling — CSV, Excel, JSON
• Working with real datasets from day one
Interview Prep Focus: Python basics for analytics — rapid-fire MCQ round
Week 2: NumPy & Pandas Core
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Tools/Tech: NumPy, Pandas
• NumPy arrays & vectorized operations
• Pandas Series & DataFrame fundamentals
• Data cleaning — missing values, duplicates, outliers
• Filtering, sorting, groupby operations
Interview Prep Focus: Live Pandas coding round
Week 3: Advanced Pandas & Data Wrangling
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• Merging, joining, concatenating datasets
• Pivot tables & cross-tabulation in Pandas
• Working with dates and time-series data
• Wrangling messy real-world datasets
Interview Prep Focus: Data-cleaning case study — messy dataset challenge
Week 4: Exploratory Data Analysis with Python
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• Univariate, bivariate, multivariate analysis
• Correlation analysis, outlier detection
• Automated EDA tools (ydata-profiling)
• Feature engineering basics
Month-End Project: End-to-end Python EDA project on a real Kaggle dataset, published on GitHub.
MONTH 2 — SQL & DATABASE ANALYTICS
Week 5: SQL Fundamentals
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Tools/Tech: MySQL/PostgreSQL
• SELECT, WHERE, ORDER BY, GROUP BY
• Joins — INNER, LEFT, RIGHT, FULL
• Aggregate functions
• Subqueries
Week 6: Advanced SQL Queries
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• Window functions — ROW_NUMBER, RANK, LAG/LEAD
• CTEs and recursive queries
• Subqueries vs joins — performance considerations
• Query optimization & indexing basics
Interview Prep Focus: Live SQL coding round (window-function heavy — the most common Data Analyst
technical test)
Week 7: Database Design & Data Modeling
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• ER diagrams, normalization
• Star schema vs snowflake schema (data warehousing)
• Fact and dimension tables
• Designing an analytics-ready database
Interview Prep Focus: 'Design a schema for X' — data modeling question
Week 8: SQL for Business Analytics
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• Cohort analysis with SQL
• RFM (Recency, Frequency, Monetary) analysis
• Time-series queries, date functions
• Real business case study with SQL
Month-End Project: Complete SQL-based business analytics project (e-commerce/SaaS dataset) — cohort
analysis + KPI dashboard queries.
MONTH 3 — STATISTICS & EXCEL FOR BUSINESS
Week 9: Statistics Foundations for Analytics
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• Descriptive statistics — mean, median, mode, variance
• Probability basics, distributions
• Correlation vs causation
• Sampling methods, margin of error
Interview Prep Focus: Statistics case-study questions
Week 10: Advanced Statistics & Hypothesis Testing
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• Z-test, T-test, Chi-square, ANOVA
• Confidence intervals
• A/B testing design & statistical significance
• Regression analysis basics
Interview Prep Focus: A/B testing case study — a favorite at product companies
Week 11: Excel for Data Analysis
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Tools/Tech: MS Excel
• Core functions & formulas for analytics
• Data cleaning — Text functions, IF, VLOOKUP/XLOOKUP
• PivotTables & PivotCharts
• Basic Excel dashboards
Interview Prep Focus: Excel functions & formula-writing practical test
Week 12: Advanced Excel & Power Query
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• Advanced formulas — INDEX-MATCH, array formulas
• Power Query — data transformation, ETL inside Excel
• What-if analysis, data validation
• Excel automation with Macros/VBA basics
Month-End Project: Excel-based sales/business dashboard with a clean data pipeline and PivotTables.
MONTH 4 — DATA VISUALIZATION & POWER BI
Week 13: Data Visualization with Python
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Tools/Tech: Matplotlib, Seaborn, Plotly Business Intelligence Phase: Turning analysis into decision-ready dashboards
• Matplotlib fundamentals
• Seaborn statistical visualizations
• Plotly for interactive charts
• Choosing the right chart for the data
Interview Prep Focus: 'Which chart would you use for this data?' questions
Week 14: Power BI — Fundamentals
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Tools/Tech: Power BI
• Power BI interface, data import & transformation
• Data modeling in Power BI (relationships)
• DAX basics — calculated columns & measures
• Building interactive reports
Interview Prep Focus: Live DAX formula-writing test
Week 15: Power BI — Advanced Dashboards
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Tools/Tech: Power BI
• Advanced DAX — time intelligence functions
• Building executive dashboards
• Row-level security, drill-through reports
• Publishing & sharing Power BI reports
Interview Prep Focus: 'Build a dashboard for X business scenario' — live task
Week 16: Tableau Fundamentals
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Tools/Tech: Tableau
• Tableau interface, connecting to data sources
• Building visualizations & dashboards
• Calculated fields, parameters
• Power BI vs Tableau — when to use which
Month-End Project: A complete interactive Power BI/Tableau dashboard for a real business scenario (sales,
marketing, or HR analytics).
MONTH 5 — ADVANCED BI & BUSINESS ANALYTICS
Week 17: Data Storytelling & Presentation
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• Principles of data storytelling
• Designing dashboards for different stakeholders
• Presenting insights to non-technical audiences
• Building a narrative from data
Interview Prep Focus: 'Present these findings to a CEO' — communication round simulation
Week 18: Marketing & Product Analytics
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• Google Analytics basics
• Funnel analysis, conversion rate optimization
• Customer segmentation (RFM, clustering basics)
• Product metrics — DAU/MAU, retention, churn
Interview Prep Focus: Product-analytics case study (common at product companies)
Week 19: Financial & Business Analytics
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• Financial statement analysis basics
• Revenue/cost analysis, forecasting basics
• Budgeting & variance analysis
• Building a financial dashboard
Week 20: Advanced Dashboards & KPI Tracking Systems
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• Designing KPI frameworks for different departments
• Advanced dashboard UX — layout, drill-downs, filters
• Automated alerting on KPI thresholds
• Combining Power BI/Excel/SQL into one reporting system
Month-End Project: A complete BI project — from raw data to a boardroom-ready dashboard with
actionable business recommendations
MONTH 6 — PREDICTIVE ANALYTICS & FORECASTING
Week 21: Introduction to Predictive Analytics
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Tools/Tech: Scikit-learn
• ML basics for analysts — when analysts actually need ML
• Linear regression for forecasting
• Classification basics — churn prediction use case
• Scikit-learn essentials for analysts
Interview Prep Focus: 'How would you predict X?' — applied reasoning questions
Week 22: Time Series Forecasting
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• Time series components, trend & seasonality
• Moving averages, exponential smoothing
• ARIMA basics for business forecasting
• Real sales/demand forecasting project
Interview Prep Focus: Forecasting model interpretation questions
Week 23: Customer Analytics & Segmentation
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• K-Means clustering for customer segmentation
• Cohort retention analysis
• Customer Lifetime Value (CLV) calculation
• Building a segmentation-based marketing strategy
Interview Prep Focus: Segmentation strategy case study
Week 24: A/B Testing & Experimentation
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• Designing A/B tests end-to-end
• Statistical significance & sample size calculation
• Analyzing A/B test results
• Common pitfalls in experimentation
Month-End Project: A predictive analytics project (churn prediction or sales forecasting) combined with a
full A/B test analysis report.
MONTH 7 — DATA ENGINEERING BASICS, CLOUD & AUTOMATION
Week 25: Data Warehousing Concepts
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• OLTP vs OLAP, data warehouse architecture
• ETL vs ELT pipelines
• Introduction to Snowflake/BigQuery
• Building a simple data pipeline
Interview Prep Focus: Data warehousing concept questions
Week 26: Cloud Analytics Tools
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Tools/Tech: BigQuery, AWS/Azure basics
• Google BigQuery — querying at scale
• AWS/Azure basics for analytics (S3, Redshift overview)
• Connecting BI tools to cloud data warehouses
• Cost & performance considerations
Interview Prep Focus: Cloud analytics tools awareness round
Week 27: Automation & Workflow Tools
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Tools/Tech: Apache Airflow (basics)
• Python automation for scheduled reporting
• Apache Airflow basics — orchestrating data pipelines
• API integration for data collection
• Building automated, self-updating dashboards
Interview Prep Focus: 'How would you automate this reporting process?'
Week 28: Git, Version Control & Collaboration
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Tools/Tech: Git/GitHub
• Git/GitHub for data projects
• Documentation best practices for analytics work
• Collaborating with data engineering & product teams
• Building a professional analytics portfolio
Month-End Project: An automated, cloud-connected reporting pipeline — data pulled automatically, cleaned,
and visualized in a live dashboard.
MONTH 8 — CAPSTONE, CASE STUDIES & PLACEMENT SPRINT
Week 29: Capstone Project Planning
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• Choosing a real-world business problem
• Data collection & problem scoping
• Planning the full analytics workflow
• Stakeholder requirement-gathering simulation
Week 30: Capstone Project Development
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• Full pipeline — SQL + Python + Excel + BI tool
• End-to-end analysis with actionable recommendations
• Building the final dashboard/report
• Peer review & feedback
Week 31: Case Study Interview Practice
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• Business case interview framework
• Guesstimate & analytical thinking questions
• Live SQL/Excel/Python problem-solving under time pressure
• Mock case-study presentations
Interview Prep Focus: Full case-study mock interview — the most common Data Analyst interview format
Week 32: Placement Sprint
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• Resume, LinkedIn & portfolio finalization (SQL/Python/Power BI/Tableau projects)
• Mock interviews — technical (SQL/Excel/Python) + case study + HR
• Curated interview question bank (SQL, Excel, statistics, case studies)
• Salary negotiation & job application strategy
Month-End Project: Final Capstone — a complete, presented, portfolio-ready business analytics case study
Requirement For This Course
Computer / Mobile
Internet Connection
Paper / Pencil
Course Includes
260 Lessons
520
Intermediate
Hindi/English
45+ Enrolled
Certificate on Completion
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Your Journey With Us
From enrollment to a career you'll enjoy
Six simple steps — that's the entire path from signing up to building a career you're genuinely excited about, with Piedocx supporting you at every stage.
Day 1Month 1–8Month 7–8
Month 7–8Month 7–8Ongoing
Start
Step 01
Enroll
Register for your course and get instant access to your LMS, mentors and community.
Day 1Step 02
Complete 8 Months
Work through the full curriculum — 8 real projects, weekly interview prep, one month at a time.
Month 1–8Step 03
Join Interview
Our placement cell lines you up with mock rounds first, then real interviews with hiring partners.
Month 7–8Step 04
Boost Your Experience
Close skill gaps with targeted practice, GitHub & resume polish, so every interview lands stronger.
Month 7–8Step 05
Get Hired
Turn interviews into offers — with negotiation support and a smooth handover into your new role.
Month 7–8
Goal
Step 06
Enjoy the Journey
Grow in your role with lifetime alumni access, referrals and upskilling — the path doesn't stop here.
OngoingSix steps. One clear path. Your journey starts the day you enroll.
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