AI-Powered Data Analytics Professional Program
AI-Powered Data Analytics Professional Program
Build industry-ready skills with practical training, expert guidance and career-focused learning.
Apply Now3 Months
120 Hours
Monday – Friday
Offline / Online
17 Modules
Course Overview
Jigsaw TechnoHub’s AI-Powered Data Analytics Course is built for people who want to turn messy data into decisions a business can actually act on. If you’re looking for a Data Analytics course in Coimbatore that goes beyond theory, this one is hands-on from the start.
You begin with the basics: analytics fundamentals, Excel, statistics, and data visualization. From there you move into SQL, Python, data preparation, Power BI and dashboards. The Professional level adds the AI side, including AI-assisted analytics, predictive models, automation, and advanced Power BI.
It's a practical AI data analytics course, with real datasets, case studies and industry projects, so you learn to collect, clean, analyze and present data the way working analysts do. Think of it as a Data Analyst with AI course with placement support, aimed at getting you job-ready.
By the end of the programme, students will:
- Understand the complete data analytics lifecycle
- Work with Excel and spreadsheet-based data
- Clean and prepare real-world datasets
- Write SQL queries to extract and analyse data
- Use Python for data analysis
- Apply statistics to business data
- Create interactive Power BI dashboards
- Perform exploratory data analysis
- Generate business insights from datasets
- Use AI tools to accelerate data analysis
- Automate repetitive analytics tasks
- Perform basic predictive analytics
- Build professional data analytics projects
- Create a job-ready analytics portfolio
COURSE MODULES
01 | Introduction to Data Analytics
This first module covers the basics of data analytics and shows how companies use data to make better decisions. It's a solid starting point for anyone beginning an AI data analytics course.
What You'll Learn
- Introduction to Data Analytics
- Data Analytics vs Data Science
- Data Analyst vs Data Scientist
- Types of Data
- Structured and Unstructured Data
- Data Analytics Lifecycle
- Data Collection
- Data Preparation
- Data Analysis
- Data Visualization
- Data Interpretation
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics – Introduction
- Prescriptive Analytics – Introduction
- Role of Data in Business Decision-Making
- Data Analytics Career Opportunities
02| Excel for Data Analytics
Here you learn to use Microsoft Excel the way analysts do at work: organizing business data, cleaning it up, analyzing it and turning it into clear visuals.
What You'll Learn
- Excel interface and data management
- Data entry and formatting
- Sorting and filtering
- Tables
- Basic and advanced formulas
- Relative and absolute references
- IF functions
- SUMIF and COUNTIF
- XLOOKUP / lookup functions
- Text functions
- Date and time functions
- Conditional formatting
- Data validation
- Removing duplicates
- Data cleaning in Excel
- Pivot Tables
- Pivot Charts
- Basic Excel dashboards
03| Statistics for Data Analytics
This module covers the statistics you need to make sense of a dataset and explain what it’s telling you, in a way that people outside the analytics team can follow.
What You'll Learn
- Introduction to Statistics
- Population and Sample
- Mean
- Median
- Mode
- Range
- Variance
- Standard Deviation
- Percentiles
- Quartiles
- Probability fundamentals
- Distributions
- Correlation
- Outliers
- Sampling
- Interpreting statistical results
- Business applications of statistics
04| Data Visualization Fundamentals
This module teaches you how to turn rows of numbers into charts and visuals that people can read at a glance and act on.
What You'll Learn
- Introduction to Data Visualization
- Importance of Data Visualization
- Choosing the right chart
- Bar Charts
- Column Charts
- Line Charts
- Pie Charts
- Scatter Plots
- Histograms
- Area Charts
- Tables
- KPIs
- Data labels
- Chart formatting
- Visual hierarchy
- Dashboard design fundamentals
- Data storytelling fundamentals
05| Beginner Data Analytics Projects
Now you put everything from the Beginner level to work on real-world datasets, so the skills you’ve built get tested on practical business problems.
Projects
- Sales Data Analysis
- Employee Data Analysis
- Student Performance Analysis
- Customer Data Analysis
Students will create:
- Clean datasets
- Excel reports
- Pivot-based analysis
- Basic dashboards
- Business insights
06 | SQL for Data Analytics
This module shows you how to pull data out of relational databases, then filter, reshape and analyze it with SQL, the skill most analyst job descriptions ask for first.
What You'll Learn
- Introduction to Databases
- Relational Databases
- Tables and Relationships
- SQL Fundamentals
- SELECT statements
- WHERE conditions
- ORDER BY
- GROUP BY
- HAVING
- Aggregate Functions
- CASE statements
- Subqueries
- Joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- UNION
- Common Table Expressions
- Window Functions – Introduction
- Data analysis using SQL
07| Python for Data Analytics
You start with Python from the ground up, then use it on practical data analysis tasks, from reading files to working with datasets in Pandas.
What You'll Learn
- Introduction to Python
- Python development environment
- Variables and Data Types
- Operators
- Conditional Statements
- Loops
- Functions
- Lists and Dictionaries
- File Handling
- Exception Handling
- Introduction to Jupyter Notebook
- Working with CSV files
- Introduction to NumPy
- Introduction to Pandas
08| Data Cleaning & Exploratory Data Analysis
Real data is rarely tidy. This module shows you how to take messy, inconsistent datasets and get them ready for analysis, then explore them to find the patterns worth acting on.
What You'll Learn
- Understanding raw datasets
- Data quality
- Missing values
- Duplicate records
- Incorrect data types
- Outlier identification
- Data transformation
- Data standardization
- Data normalization
- Data filtering
- Data aggregation
- Data merging
- Data manipulation using Pandas
- Exploratory Data Analysis
- Identifying patterns and trends
- Generating analytical insights
09| Power BI Fundamentals
Here you get hands-on with Power BI: connecting to your data, cleaning and shaping it, and building interactive reports that business teams can explore on their own.
What You'll Learn
- Introduction to Power BI
- Power BI Desktop
- Connecting data sources
- Excel data
- CSV data
- Database connections
- Data transformation
- Power Query
- Data cleaning
- Data relationships
- Data models
- Calculated columns
- Measures
- Basic DAX
- Charts and visuals
- Filters
- Slicers
- Interactive reports
- Dashboard fundamentals
10| Business Intelligence & Dashboard Design
This module is about starting from what the business actually needs and building dashboards that answer it, clear enough that a manager can use them without any explanation.
What You'll Learn
- Introduction to Business Intelligence
- Business KPIs
- Understanding business requirements
- Identifying analytical questions
- Dashboard planning
- Data storytelling
- Interactive dashboards
- Drill-downs
- Drill-throughs
- Filters and slicers
- KPI cards
- Trend analysis
- Comparative analysis
- Dashboard usability
- Dashboard design principles
- Presenting business insights
11| Intermediate Data Analytics Projects
You bring SQL, Python, Excel and Power BI together to build complete analytics projects, taking each one from raw data all the way to a finished dashboard.
Projects
- Sales Performance Dashboard
- Customer Analysis Dashboard
- HR Analytics Dashboard
- E-commerce Analytics
- Financial Performance Dashboard
- Marketing Campaign Analysis
Each project should include:
Data Cleaning → Data Analysis → Visualization → Dashboard → Business Insights
12 | Advanced Power BI & DAX
This module takes your Power BI skills to a professional level, with stronger data models, DAX calculations and dynamic reports of the kind real business intelligence teams build.
What You'll Learn
- Advanced Power Query
- Data transformation techniques
- Advanced data modelling
- Star schema fundamentals
- Fact and dimension tables
- Relationships
- Calculated columns
- Measures
- DAX fundamentals
- DAX functions
- CALCULATE
- FILTER
- Time intelligence
- Date tables
- YTD, MTD and YoY analysis
- Advanced KPIs
- Dynamic dashboards
- Drill-through reports
- Power BI report optimization
13| AI-Powered Data Analytics
This is where the AI-powered data analytics course gets its edge. You learn how AI can speed up analysis, surface insights faster and take the grunt work out of reporting, while you stay in charge of the thinking.
What You'll Learn
- Introduction to AI in Data Analytics
- AI-assisted data exploration
- AI-assisted data cleaning
- AI-generated SQL queries
- AI-assisted Python analysis
- AI-assisted formula generation
- AI-powered insight generation
- AI-assisted visualization
- AI-powered data storytelling
- Natural language data analysis
- AI-assisted report generation
- AI-powered anomaly detection
- AI-assisted business recommendations
- Using AI to improve analyst productivity
- Responsible use of AI in analytics
14| Predictive Analytics Fundamentals
This module introduces the techniques businesses use to forecast what’s coming next, from sales and demand to customer churn, and how to read the results with confidence.
What You'll Learn
- Introduction to Predictive Analytics
- Predictive vs Descriptive Analytics
- Business Forecasting
- Trend Analysis
- Time Series Fundamentals
- Moving Averages
- Forecasting Techniques
- Regression Fundamentals
- Classification Fundamentals
- Customer Churn Prediction
- Sales Forecasting
- Demand Forecasting
- Risk Analysis
- Model evaluation fundamentals
- Interpreting predictive results
Tools Introduced
- Python
- Pandas
- Scikit-learn – Introduction
- Power BI
15| Data Automation & AI Workflows
Analysts lose hours to the same repetitive tasks every week. This module shows you how to automate them, from data collection to scheduled reports, so you can spend your time on the analysis itself.
What You'll Learn
- Introduction to Data Automation
- Automated data collection
- Automated data cleaning
- Automated reporting
- Scheduled data refresh
- Automated dashboard updates
- AI-assisted reporting
- Automated insight generation
- Excel automation fundamentals
- Python automation
- API fundamentals
- Connecting data sources
- Workflow automation
- AI-powered reporting workflows
- Error handling
- Monitoring automated workflows
Tools Introduced
- Python
- Power Automate
- Make / Zapier – Introduction
- APIs
- AI tools
16| Advanced Analytics & Business Intelligence
This module looks at how experienced analysts use data to inform strategy, across areas like sales, marketing, finance and HR, and how to present their findings so stakeholders actually act on them
What You'll Learn
- Advanced business analytics
- Customer analytics
- Marketing analytics
- Sales analytics
- Financial analytics
- HR analytics
- Product analytics
- Operational analytics
- Customer segmentation
- Cohort analysis
- Funnel analysis
- Retention analysis
- Profitability analysis
- KPI frameworks
- Business performance analysis
- Data-driven decision-making
- Advanced data storytelling
- Presenting insights to stakeholders
17| Professional Data Analytics Capstone & Career Preparation
To finish the program, you build one complete analytics project from start to finish, using data preparation, SQL, Python, Power BI and AI together. You also get the career preparation that rounds out a Data Analyst with AI course with placement support, so you’re ready for interviews as well as the job itself.
Capstone Project Process
Business Problem → Data Collection → Data Cleaning → SQL Analysis → Exploratory Analysis → KPI Development → Power BI Dashboard → AI-Assisted Insights → Predictive Analysis → Business Recommendations → Final Presentation
Capstone Project Options
Students can develop projects such as:
- E-commerce Business Analytics
- Sales & Revenue Analytics
- Customer Churn Analytics
- Marketing Performance Analytics
- HR Workforce Analytics
- Financial Analytics
- Healthcare Analytics
- Retail Analytics
- Supply Chain Analytics
- Product Analytics
What Students Will Create
- Cleaned datasets
- SQL analysis
- Python analysis
- Interactive Power BI dashboard
- KPI report
- AI-generated analytical insights
- Business recommendations
- Professional analytics presentation
- Final capstone report
Software & Tools Covered
Throughout the Professional Program, students will gain practical experience with:
- Microsoft Excel
- Advanced Excel
- Power BI
- Power Query
- DAX
- SQL
- MySQL / SQL databases
- Python
- Jupyter Notebook
- Google Colab
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn – Introduction
- Power Automate
- Make / Zapier – Introduction
- REST APIs – Introduction
- ChatGPT
- Google Gemini
- Microsoft Copilot
- AI-powered analytics tools
- AI-assisted reporting tools
Career Opportunities
After completing the Professional Program, learners can pursue roles such as:
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Data Analyst
- Deep Learning Engineer
- NLP Engineer
- Computer Vision Engineer
- AI Application Developer
- MLOps Engineer (Entry Level)
- Business Intelligence Analyst
- Python Developer (AI Focus)
- Generative AI Developer
Enquire Now
Ready to build your data analytics career? Learn AI-powered data analytics through practical projects, real-world datasets and career-focused training.
Placements
Simple steps, Limitless Possibilities
Joseph Price
Data Science
Paul Shajan
Digital Marketing
Thomas
Digital Marketing
Course Cetificate
Certificate
The AI-Powered Data Analytics Professional Program at Jigsaw TechnoHub helps learners build practical skills in Excel, SQL, Python, Power BI, Predictive Analytics, automation and AI-assisted reporting, so they’re ready for real analyst roles. .
- Clean and analyze data with Excel and SQL
- Understand statistics and data visualization
- Work with Python and Pandas for analysis
- Build interactive Power BI dashboards
- Use AI tools to speed up analysis
- Forecast trends with predictive analytics
- Automate reports and data workflows
- Present insights and business recommendations
Ready to Build Your Future?
Your journey from graduate to professional starts here.Join Jigsaw TechnoHub and gain the skills, confidence, and industry exposure needed to succeed in today's competitive job market.