Learn to analyze data, find patterns, generate insights and automate analytical work with Artificial Intelligence – from Generative AI and prompt engineering to Machine Learning, NLP and AI-assisted Python, SQL & Excel.
The AI course is designed for students, graduates, job seekers and working professionals who want to understand and apply Artificial Intelligence techniques in Data Science and business analytics.
53 ModulesStep-by-step syllabus
4 + 1Projects + capstone
FlexibleMorning · Evening · Weekend
ISO & NSDCQR-verified certificate
Students join this course from Dahisar, Vasai, Virar, Palghar and Boisar, attending classes at whichever of our Mira Road, Bhayandar or Boisar branches is closest to them.
Build a clear picture of what AI is, where it came from and where it is used today.
What is Artificial Intelligence?
Evolution of Artificial Intelligence
History of AI
AI and Modern Technology
AI in Everyday Life
AI in Business
AI in Data Science
AI in Analytics
Applications of AI
Advantages of AI
Limitations of AI
Challenges in AI
Future Scope of AI
AI in Different Industries
Applications of AI
Business Analytics
Banking & Finance
Healthcare
Education
E-Commerce
Marketing
Manufacturing
Retail
Customer Service
Human Resources
Cybersecurity
Logistics
Recommendation Systems
02AI Foundations
AI and Data Science
20 topics
Understand the relationship between Artificial Intelligence, Data Science, Machine Learning and Data Analytics.
AI vs Data Science
AI vs Machine Learning
Machine Learning as a part of AI
Data Science and AI
AI-Based Data Analysis
Predictive Analytics
Intelligent Automation
AI-Assisted Decision Making
AI Data Workflows
Role of Data in Artificial Intelligence
Data Science Workflow with AI
Data Collection
Data Cleaning
Data Exploration
Data Analysis
Feature Preparation
Model Development
Prediction
Insight Generation
Reporting
AI-Assisted Decision Making
03AI Foundations
Fundamentals of Machine Learning
16 topics
Understand the basic Machine Learning concepts required for practical AI applications.
What is Machine Learning?
Supervised Learning
Unsupervised Learning
Classification
Regression
Clustering
Training Data
Testing Data
Features
Target Variables
Model Training
Model Prediction
Model Evaluation
Overfitting
Underfitting
Model Selection
Phase 02 · Python & Data ToolkitModules 04–09
04Python & Data Toolkit
Python for AI
21 topics
Learn the Python concepts required for AI and Data Science applications.
Python Fundamentals
Variables
Data Types
Operators
Conditional Statements
Loops
Functions
Lists
Tuples
Dictionaries
Sets
File Handling
Exception Handling
Modules
Packages
Working with Libraries
Python Libraries
NumPy
Pandas
Matplotlib
Seaborn
Scikit-learn
05Python & Data Toolkit
NumPy for AI & Data Science
16 topics
Learn numerical computing concepts used in AI and Data Science.
NumPy Arrays
One-Dimensional Arrays
Multi-Dimensional Arrays
Array Indexing
Array Slicing
Array Reshaping
Array Operations
Mathematical Operations
Statistical Functions
Mean
Median
Standard Deviation
Variance
Minimum and Maximum
Broadcasting
Boolean Indexing
06Python & Data Toolkit
Pandas for AI Data Processing
16 topics
Learn how to prepare and manipulate datasets for AI applications.
Series
DataFrames
Importing Data
CSV Files
Excel Files
Data Inspection
Filtering Data
Sorting Data
Grouping Data
Aggregation
Merging Data
Joining Data
Data Transformation
Date and Time Data
Creating New Features
Dataset Preparation
07Python & Data Toolkit
Data Preparation for AI
13 topics
Learn how data is prepared before applying AI techniques.
Understanding Raw Data
Data Quality
Missing Values
Duplicate Records
Incorrect Data
Data Types
Data Transformation
Data Standardization
Data Normalization
Categorical Data
Numerical Data
Feature Preparation
Dataset Validation
08Python & Data Toolkit
Exploratory Data Analysis with AI
11 topics
Learn how AI tools can assist in understanding and analyzing datasets — and how AI can help analysts ask questions about data and generate initial insights.
Dataset Exploration
Descriptive Statistics
Data Summarization
Pattern Identification
Trend Analysis
Correlation Analysis
Outlier Identification
Data Distribution
Relationship Analysis
Automated Data Insights
AI-Assisted Data Interpretation
09Python & Data Toolkit
Data Visualization with AI
13 topics
Learn how AI can assist in creating and interpreting data visualizations.
Data Visualization Fundamentals
Charts and Graphs
Bar Charts
Line Charts
Pie Charts
Scatter Plots
Histograms
Box Plots
Heatmaps
Correlation Visualization
AI-Assisted Chart Selection
AI-Assisted Visualization Analysis
Data Storytelling
Phase 03 · Generative AI & LLMsModules 10–12
10Generative AI & LLMs
Introduction to Generative AI
12 topics
Understand the fundamentals of Generative AI and its applications.
What is Generative AI?
Traditional AI vs Generative AI
Generative AI Applications
Text Generation
Image Generation
Code Generation
Data Generation
Document Summarization
Content Generation
AI Assistants
Generative AI in Business
Generative AI in Data Science
11Generative AI & LLMs
Large Language Models
12 topics
Understand the basic concepts behind modern AI language models and how they assist with analytical and productivity tasks.
What is a Language Model?
Introduction to Large Language Models
How Language Models Process Text
Tokens
Context
Prompts
Responses
Model Limitations
Hallucinations
Knowledge Limitations
AI-Assisted Research
AI-Assisted Data Analysis
12Generative AI & LLMs
Prompt Engineering
22 topics
Learn how to communicate effectively with AI systems to obtain useful and reliable outputs.
What is Prompt Engineering?
Prompt Structure
Clear Instructions
Context
Role-Based Prompts
Task-Based Prompts
Output Formatting
Examples in Prompts
Step-by-Step Instructions
Constraints
Prompt Refinement
Prompt Testing
Prompt Optimization
Data Science Prompting
Generate data analysis questions
Explain datasets
Generate formulas
Generate Python code
Explain Python code
Generate SQL queries
Summarize analytical results
Create report structures
Explain Machine Learning concepts
Phase 04 · AI-Assisted Data WorkModules 13–17
13AI-Assisted Data Work
AI-Assisted Data Analysis
17 topics
Learn how AI tools can support common Data Science tasks.
Dataset Understanding
Data Summarization
Automated Data Analysis
Finding Patterns
Identifying Trends
Identifying Anomalies
Generating Analytical Questions
Data Interpretation
Automated Insights
Report Generation
Business Question Analysis
Practical Applications
Sales Data Analysis
Customer Data Analysis
Employee Data Analysis
Financial Data Analysis
Marketing Data Analysis
E-Commerce Data Analysis
14AI-Assisted Data Work
AI for Data Cleaning
10 topics
Learn how AI can assist with data preparation and cleaning — using AI as an assistant while keeping human verification of every data transformation.
Identifying Missing Values
Identifying Duplicate Data
Detecting Inconsistent Values
Data Standardization
Text Cleaning
Data Formatting
Data Transformation
Identifying Possible Data Errors
Generating Data Cleaning Code
AI-Assisted Data Validation
15AI-Assisted Data Work
AI-Assisted Python Programming
12 topics
Learn how AI can assist with Python-based Data Science tasks.
Generating Python Code
Explaining Python Code
Debugging Python Code
Improving Existing Code
Generating Functions
Converting Requirements into Code
Finding Programming Errors
Code Documentation
Code Optimization – Introduction
Generating Data Analysis Scripts
Generating Visualization Code
Generating Machine Learning Code
16AI-Assisted Data Work
AI-Assisted SQL for Data Science
19 topics
Learn how AI can assist with database querying and SQL analysis.
Generating SQL Queries
Explaining SQL Queries
Correcting SQL Errors
SELECT Queries
WHERE Conditions
GROUP BY
ORDER BY
Aggregate Functions
JOIN Queries
Subqueries
Common Table Expressions – Introduction
Data Analysis Queries
Query Optimization – Introduction
Practical Applications
Sales Analysis
Customer Analysis
Product Analysis
Revenue Analysis
Employee Analysis
Business Reporting
17AI-Assisted Data Work
AI-Assisted Excel & Spreadsheet Analysis
11 topics
Learn how AI can improve productivity while working with spreadsheet data.
AI-Assisted Excel Formulas
Formula Generation
Formula Explanation
Formula Error Identification
Data Summarization
Data Cleaning Assistance
Chart Suggestions
Report Generation
Business Insights
Automated Analysis
AI-Assisted Spreadsheet Productivity
Phase 05 · Machine LearningModules 18–21
18Machine Learning
AI for Predictive Analytics
16 topics
Understand how AI and Machine Learning can be used for prediction.
Predictive Analytics
Historical Data
Prediction Problems
Regression
Classification
Forecasting Concepts
Predictive Features
Model Training
Model Evaluation
Prediction Interpretation
Practical Applications
Sales Prediction
Customer Churn Prediction
Demand Prediction
Revenue Prediction
Employee Attrition Prediction
Customer Response Prediction
19Machine Learning
AI-Based Classification
19 topics
Learn how AI models can classify data into different categories.
Classification Fundamentals
Binary Classification
Multi-Class Classification
Classification Features
Target Classes
Training Classification Models
Prediction
Classification Evaluation
Accuracy
Precision
Recall
F1 Score
Confusion Matrix
Applications
Customer Churn
Spam Detection
Customer Segmentation
Loan Classification
Product Classification
Customer Response Prediction
20Machine Learning
AI-Based Regression
16 topics
Learn how AI models can predict numerical outcomes.
Regression Fundamentals
Numerical Prediction
Linear Regression
Multiple Regression
Prediction
Model Training
Model Evaluation
Mean Absolute Error
Mean Squared Error
Root Mean Squared Error
R² Score
Applications
Sales Prediction
Price Prediction
Revenue Prediction
Demand Prediction
Salary Prediction
21Machine Learning
AI-Based Clustering
14 topics
Learn how AI can identify groups and patterns in datasets.
Unsupervised Learning
Clustering
K-Means
Cluster Formation
Customer Segmentation
Similarity Analysis
Cluster Interpretation
Elbow Method
Cluster Evaluation
Practical Applications
Customer Segmentation
Product Segmentation
Market Segmentation
Store Segmentation
Customer Behavior Analysis
Phase 06 · NLP & Text AIModules 22–25
22NLP & Text AI
Natural Language Processing
13 topics
Understand how AI systems work with human language.
Introduction to NLP
Text Data
Natural Language Processing Applications
Text Cleaning
Tokenization
Stop Words
Stemming
Lemmatization
Word Frequency
Text Classification
Sentiment Analysis
Text Summarization
Document Analysis
23NLP & Text AI
Sentiment Analysis
15 topics
Learn how AI can analyze the emotional or opinion-related characteristics of text.
Introduction to Sentiment Analysis
Positive Sentiment
Negative Sentiment
Neutral Sentiment
Text Preparation
Sentiment Classification
Customer Feedback Analysis
Review Analysis
Social Media Text Analysis
Business Applications
Practical Applications
Product Reviews
Customer Feedback
Service Reviews
Survey Responses
Brand Feedback
24NLP & Text AI
Text Classification
9 topics
Learn how AI can classify documents and text into predefined categories.
Text Classification
Text Preprocessing
Feature Extraction
Classification Models
Document Categorization
Spam Detection
News Classification
Customer Query Classification
Support Ticket Classification
25NLP & Text AI
AI-Powered Text Summarization
9 topics
Learn how AI can summarize large amounts of textual information.
Text Summarization
Extractive Summarization
Abstractive Summarization
Document Summarization
Report Summarization
Meeting Notes
Research Summaries
Business Document Summaries
Customer Feedback Summaries
Phase 07 · BI, Reporting & InsightsModules 26–31
26BI, Reporting & Insights
AI for Business Intelligence
11 topics
Learn how AI can support business intelligence and analytical decision-making.
AI in Business Intelligence
Automated Insights
Business Question Generation
Trend Detection
Performance Analysis
KPI Analysis
Sales Analytics
Customer Analytics
Financial Analytics
Marketing Analytics
Management Reporting
27BI, Reporting & Insights
AI for Business Reporting
10 topics
Learn how AI can assist in preparing professional analytical reports.
Report Structure
Data Summarization
Executive Summaries
KPI Reporting
Trend Reporting
Business Insights
Automated Narrative Generation
Report Writing
Data-Based Recommendations
Management Presentation Preparation
28BI, Reporting & Insights
AI-Assisted Data Storytelling
9 topics
Learn how to communicate data insights using AI-assisted techniques.
What is Data Storytelling?
Finding the Main Insight
Identifying Important Trends
Explaining Data
Creating Analytical Narratives
Creating Executive Summaries
Turning Analysis into Business Stories
AI-Assisted Presentation Content
Communicating Complex Data Simply
29BI, Reporting & Insights
AI for Data Visualization
10 topics
Learn how AI can support visualization planning and interpretation.
Selecting Appropriate Charts
Visualization Recommendations
Chart Interpretation
Trend Identification
Pattern Identification
Dashboard Planning
KPI Visualization
Interactive Reporting
AI-Assisted Dashboard Ideas
Visualization Storytelling
30BI, Reporting & Insights
AI for Anomaly Detection
13 topics
Learn how AI and Machine Learning can help identify unusual patterns in data.
What is Anomaly Detection?
Normal vs Unusual Data
Outliers
Statistical Approaches
Machine Learning Approaches
Anomaly Identification
Transaction Analysis
Business Data Monitoring
Applications
Unusual Transactions
Sales Anomalies
Customer Behavior
Network Activity
Inventory Analysis
31BI, Reporting & Insights
AI Recommendation Systems
15 topics
Understand the fundamentals of recommendation systems.
What is a Recommendation System?
Recommendation Applications
Product Recommendations
Content Recommendations
Customer Preferences
User Behavior
Similarity
Collaborative Filtering – Introduction
Content-Based Recommendations – Introduction
Applications
E-Commerce
Movies
Music
Products
Online Learning
Content Platforms
Phase 08 · Automation, Agents & ML AssistModules 32–37
32Automation, Agents & ML Assist
AI Automation for Data Science
9 topics
Learn how AI can assist in automating repetitive Data Science activities.
AI-Based Automation
Automated Data Summaries
Automated Report Generation
Automated Data Cleaning Assistance
Automated Code Generation
Automated Documentation
Automated Insight Generation
Repetitive Task Automation
AI-Assisted Workflow Design
33Automation, Agents & ML Assist
AI Agents – Introduction
11 topics
Understand the basic concept of AI agents and their potential applications.
What is an AI Agent?
AI Agent vs Chatbot
AI Agent Components
Goals and Tasks
Tools and Actions
Context
Automated Workflows
AI Agent Applications in Data Science
Research Assistance
Data Analysis Assistance
Reporting Assistance
34Automation, Agents & ML Assist
AI Tools for Data Science
8 topics
Get introduced to the categories of AI tools that assist Data Science workflows — and learn to pick the right tool for each task.
Tool Categories
AI Chat Assistants
AI Coding Assistants
AI Data Analysis Tools
AI Research Tools
AI Visualization Tools
AI Documentation Tools
Generative AI Platforms
AI Productivity Tools
35Automation, Agents & ML Assist
AI-Assisted Machine Learning
10 topics
Learn how AI can support different stages of Machine Learning development.
Problem Definition
Dataset Understanding
Feature Suggestions
Data Cleaning Assistance
Model Selection Assistance
Code Generation
Model Evaluation Explanation
Error Analysis
Model Documentation
Result Interpretation
36Automation, Agents & ML Assist
AI for Feature Engineering
10 topics
Learn how AI can assist in identifying and creating useful features.
Understanding Features
Feature Selection
Feature Creation
Feature Transformation
AI-Assisted Feature Suggestions
Date-Based Features
Customer-Based Features
Sales-Based Features
Behavioral Features
Feature Interpretation
37Automation, Agents & ML Assist
AI for Model Interpretation
8 topics
Learn how AI can help explain Machine Learning results.
Understanding Predictions
Feature Importance
Model Results
Prediction Explanation
Error Analysis
Model Comparison
Business Interpretation
AI-Assisted Model Documentation
Phase 09 · Responsible AI & ResearchModules 38–41
38Responsible AI & Research
Responsible AI
12 topics
Understand important considerations when using Artificial Intelligence.
Responsible AI
AI Accuracy
Data Quality
Bias in Data
Bias in AI Systems
Privacy
Security
Transparency
Explainability
Human Oversight
Responsible Use of AI
Verification of AI-Generated Results
39Responsible AI & Research
AI Limitations & Hallucinations
11 topics
Understand why AI-generated information must be checked and validated.
AI Hallucinations
Incorrect AI Responses
Outdated Information
Misinterpretation
Calculation Errors
Coding Errors
Data Quality Problems
Verification Techniques
Fact Checking
Human Review
Reliable AI Workflows
40Responsible AI & Research
AI Data Privacy & Security
10 topics
Learn important principles for handling data while using AI tools.
Data Privacy
Sensitive Information
Confidential Business Data
Personal Information
Safe Data Handling
Data Sharing Risks
Access Control
Secure AI Usage
Organizational AI Policies
Responsible Data Usage
41Responsible AI & Research
AI-Assisted Research
10 topics
Learn how AI can support research and information analysis.
Research Question Generation
Information Summarization
Document Analysis
Research Organization
Comparison of Information
Note Preparation
Research Assistance
Source Verification
Identifying Information Gaps
AI-Assisted Report Preparation
Phase 10 · Domain AnalyticsModules 42–46
42Domain Analytics
AI for Customer Analytics
9 topics
Learn how AI can be applied to customer-related datasets.
Customer Data Analysis
Customer Segmentation
Customer Behavior
Customer Churn
Customer Lifetime Value – Introduction
Customer Preferences
Customer Feedback
Customer Classification
Customer Prediction
43Domain Analytics
AI for Sales Analytics
10 topics
Learn how AI can assist sales teams and organizations in analyzing sales data.
Sales Data Analysis
Sales Trend Analysis
Sales Forecasting
Product Performance
Salesperson Performance
Regional Sales Analysis
Customer Sales Analysis
Target vs Achievement
Revenue Prediction
Sales Reporting
44Domain Analytics
AI for Marketing Analytics
10 topics
Learn how AI can be used to analyze marketing data.
Marketing Data
Customer Segmentation
Campaign Analysis
Customer Response
Lead Analysis
Conversion Analysis
Marketing Performance
Customer Behavior
Sentiment Analysis
Marketing Prediction
45Domain Analytics
AI for Financial Data Analysis
10 topics
Understand AI applications in financial and business datasets.
Financial Data Analysis
Revenue Analysis
Expense Analysis
Profit Analysis
Transaction Analysis
Trend Detection
Forecasting
Anomaly Detection
Risk Analysis – Introduction
Financial Reporting
46Domain Analytics
AI for E-Commerce Analytics
10 topics
Learn how AI can support e-commerce data analysis.
Customer Analysis
Product Analysis
Sales Analysis
Order Analysis
Customer Segmentation
Product Recommendations
Customer Churn
Review Analysis
Sentiment Analysis
Sales Prediction
Phase 11 · Projects & CareerModules 47–53
47Projects & Career
AI Project – Customer Analytics
9 topics
Develop a practical AI-assisted customer analytics project.
Project Includes
Customer Dataset
Data Cleaning
Exploratory Data Analysis
Customer Segmentation
Customer Behavior Analysis
Churn Analysis
AI-Assisted Insights
Visualization
Business Report
48Projects & Career
AI Project – Sales Analytics
10 topics
Develop an AI-assisted sales analysis project.
Project Includes
Sales Dataset
Data Preparation
Sales Analysis
Product Analysis
Regional Analysis
Salesperson Analysis
Trend Analysis
Sales Prediction
AI-Assisted Reporting
Business Dashboard Concepts
49Projects & Career
AI Project – Customer Sentiment Analysis
9 topics
Develop a project for analyzing customer reviews and feedback.
Project Includes
Customer Review Dataset
Text Cleaning
Text Processing
Sentiment Analysis
Positive and Negative Review Analysis
Customer Feedback Classification
Visualization
AI-Assisted Summary
Business Insights
50Projects & Career
AI Project – Business Data Analysis
13 topics
Complete an end-to-end AI-assisted Data Science project.
Project Workflow
Business Problem
Data Collection
Data Preparation
Data Cleaning
Exploratory Data Analysis
Feature Preparation
AI-Assisted Analysis
Machine Learning
Model Evaluation
Insight Generation
Visualization
Report Generation
Business Presentation
51Projects & Career
AI Capstone Project
15 topics
Complete a comprehensive project combining everything learned — and explain its methodology, data, AI techniques, results and business relevance.
Capstone Project Includes
Problem Identification
Dataset Selection
Data Collection
Data Cleaning
Exploratory Data Analysis
Feature Engineering
AI-Assisted Analysis
Machine Learning
Predictive Analysis
Data Visualization
AI-Assisted Reporting
Result Interpretation
Business Insights
Final Documentation
Project Presentation
52Projects & Career
Practical AI Exercises
14 topics
Hands-on exercises performed throughout the course.
Exercises Include
Generate Python code using AI
Debug Python programs using AI
Generate SQL queries using AI
Analyze datasets using AI
Generate Excel formulas using AI
Summarize datasets
Generate data insights
Create analytical questions
Analyze customer reviews
Perform sentiment analysis
Create business reports
Generate data visualizations
Explain Machine Learning models
Create AI-assisted presentations
53Projects & Career
AI Interview Preparation
20 topics
Prepare for common AI and Data Science interview questions.
Interview Topics
What is Artificial Intelligence?
What is Machine Learning?
AI vs Machine Learning
AI vs Data Science
What is Generative AI?
What are Large Language Models?
What is Prompt Engineering?
What is NLP?
What is Sentiment Analysis?
What is Predictive Analytics?
What is Classification?
What is Regression?
What is Clustering?
What is Data Leakage?
What is Overfitting?
What is Model Evaluation?
What are AI Hallucinations?
What is Responsible AI?
How can AI assist Data Scientists?
How should AI-generated results be verified?
Course complete! Clear your final assessment and earn your ISO 9001:2015 & NSDC-authorised TIIT certificate.
03Learn by building
Real-World AI Projects
Every project follows the same professional workflow, from business problem to business presentation:
01Business Problem
02Data Collection
03Data Preparation
04Data Cleaning
05Exploratory Data Analysis
06Feature Preparation
07AI-Assisted Analysis
08Machine Learning
09Model Evaluation
10Insight Generation
11Visualization
12Report Generation
13Business Presentation
Module 47
Customer Analytics
Segment customers, analyze behaviour and churn, then turn AI-assisted insights into a business report.
Customer Dataset
Data Cleaning
Exploratory Data Analysis
Customer Segmentation
Module 48
Sales Analytics
Analyze products, regions and salespeople, spot trends, predict sales and plan a business dashboard.
Sales Dataset
Data Preparation
Sales Analysis
Product Analysis
Module 49
Customer Sentiment Analysis
Clean and process real reviews, classify feedback as positive or negative, and summarise it with AI.
Customer Review Dataset
Text Cleaning
Text Processing
Sentiment Analysis
Module 50
Business Data Analysis
An end-to-end project: from a business problem to a Machine Learning model and a business presentation.
Business Problem
Data Collection
Data Preparation
Data Cleaning
Module 51 · Capstone
AI Capstone Project
Complete a comprehensive project combining everything learned — and explain its methodology, data, AI techniques, results and business relevance.
Problem Identification
Dataset Selection
Data Collection
Data Cleaning
Exploratory Data Analysis
Feature Engineering
AI-Assisted Analysis
Machine Learning
Predictive Analysis
Data Visualization
AI-Assisted Reporting
Result Interpretation
Business Insights
Final Documentation
Project Presentation
04Your new toolkit
Skills You Will Learn
Artificial Intelligence
AI Fundamentals
AI Applications
Generative AI
Large Language Models
AI Assistants
AI Automation
Data Science
Data Preparation
Data Cleaning
Exploratory Data Analysis
Data Visualization
Predictive Analytics
Business Analytics
Programming
Python
NumPy
Pandas
Scikit-learn
AI Productivity
Prompt Engineering
AI-Assisted Coding
AI-Assisted SQL
AI-Assisted Excel
AI-Assisted Data Analysis
AI-Assisted Reporting
Machine Learning
Regression
Classification
Clustering
Model Evaluation
Feature Engineering
Predictive Modelling
Natural Language Processing
Text Processing
Text Classification
Sentiment Analysis
Text Summarization
Document Analysis
05Your certificate
Certification
Official & verifiable
On successful completion, you receive an official TIIT Computer Education certificate for the AI Course.
ISO 9001:2015 Certified & NSDC Authorized Training Center
Unique certificate number with a scannable QR verification code
The skills developed in this course support entry-level and foundational roles such as:
AI Trainee
AI/ML Trainee
Data Analyst
Junior Data Scientist
Data Science Intern
AI Data Analyst
Business Analyst
Data Analytics Executive
Machine Learning Trainee
AI Operations Executive
Research Assistant
Business Intelligence Executive
Placement assistance per TIIT's placement policy – resume building, interview preparation and job referrals. Career requirements vary by organization, and advanced roles may need more education, experience and specialised skills.
07The TIIT advantage
Why TIIT Computer Education?
Expert Guidance
Learn from experienced trainers who bring real industry practice into every session.
Hands-on Learning
Spend most of your time in the lab building real projects, not just watching slides.
Recognized Certification
Earn an ISO 9001:2015 & NSDC-recognized certificate valued by employers.
Placement Assistance
Get support with resume building, interview prep and job referrals.
Flexible Batches
Choose weekday, weekend or evening batches that fit your schedule.
Modern Infrastructure
Learn in well-equipped labs with the same tools this course actually uses.
Learning methodology
A practical, application-oriented way to learn AI
Eight habits you build in every module, from the first class to the capstone.
01
Learn
Understand the fundamentals of Artificial Intelligence and its applications in Data Science.
02
Practice
Apply concepts through Python, data analysis and AI exercises.
03
Analyze
Work with datasets and identify trends, patterns and relationships.
04
Build
Create AI-assisted analytical solutions and Machine Learning models.
05
Automate
Explore how AI can reduce repetitive data and reporting tasks.
06
Evaluate
Verify AI-generated outputs and evaluate Machine Learning results.
07
Interpret
Convert analytical results into meaningful business insights.
08
Present
Prepare reports, visualizations and presentations using AI-assisted workflows.
Is this course for you?
Who can join, what you need & why AI
Who can join?
This course is suitable for:
Students
College Graduates
Job Seekers
Working Professionals
Data Science Aspirants
Data Analyst Aspirants
Business Analysts
Python Learners
Machine Learning Learners
Digital Professionals
Business Owners
Researchers
Analytics Professionals
Computer Science Students
Engineering Students
Mathematics Students
Statistics Students
Anyone interested in AI & Data Science
Prerequisites
Basic computer knowledge is recommended. Preferably, basic knowledge of:
Computer Operations
Basic Python
Basic Mathematics
Basic Statistics
Basic Data Analysis
Already know Python, SQL, Excel or Data Science? Use this course to add practical AI capabilities to your existing skills.
Why learn AI?
AI is increasingly built into Data Science, analytics, software development and business operations. Organizations use it to:
Analyze data
Generate insights
Automate repetitive tasks
Improve productivity
Support predictions
Analyze text
Generate reports
Assist programming
Support business decisions
Build intelligent applications
AI knowledge also complements existing skills in Python, SQL, Excel, Data Analytics and Machine Learning.
Join the AI course near you
The same AI syllabus, trainers' standards and certificate are offered at every TIIT branch. Find the branch nearest to where you live:
Artificial Intelligence is a field of computing focused on developing systems that can perform tasks involving capabilities such as pattern recognition, prediction, language processing and decision support.
02
Is this AI course suitable for beginners?
Yes. The course starts with AI fundamentals and progressively introduces Data Science, Generative AI, Machine Learning and practical AI applications.
03
Do I need Python knowledge?
Basic Python knowledge is recommended for the programming and Data Science portions of the course. The course also includes a dedicated Python for AI module.
04
Will I learn Generative AI?
Yes. The course covers Generative AI, Large Language Models, prompt engineering and practical applications.
05
Will I learn Prompt Engineering?
Yes. Students will learn how to create structured prompts, provide context, specify outputs and refine prompts for Data Science tasks.
06
Will I learn AI-assisted Python and SQL?
Yes. Students learn how AI can assist with Python code generation, explanation, debugging and Data Science programming tasks, as well as AI-assisted SQL query generation, explanation, debugging and data analysis.
07
Will I learn Machine Learning?
Yes. The course introduces important Machine Learning concepts including regression, classification, clustering, model evaluation and predictive analytics.
08
Will I learn Natural Language Processing?
Yes. The course includes text processing, sentiment analysis, text classification and text summarization.
09
Will I work on projects?
Yes. Practical projects include Customer Analytics, Sales Analytics, Customer Sentiment Analysis, an end-to-end Business Data Analysis project and an AI capstone project.
10
Will AI-generated results always be correct?
No. AI systems can produce incorrect, incomplete or misleading outputs. Students learn the importance of verification, data quality, human review and responsible AI usage.
11
Will I receive a certificate?
Students who successfully complete the course receive a certificate according to TIIT Computer Education's certification terms. TIIT is an ISO 9001:2015 certified, NSDC-authorised training centre and every certificate carries a QR code that anyone can verify online.
12
Is placement assistance available?
Placement assistance may be available according to TIIT Computer Education's applicable placement policies and terms, including help with resume building and interview preparation.
13
What are the AI course fees and batch timings in Mira Road?
Fees and duration depend on the batch, branch and any ongoing offer, so we share the exact current details on call or WhatsApp at +91 90768 32616. Instalment options are available – ask the counsellor during your free demo.
14
I live in Dahisar, Vasai, Virar or Palghar – where can I join the AI course?
Dahisar and Kashimira students attend our Mira Road head office (opposite Mira Road station, East). Naigaon, Vasai, Nalasopara and Virar students usually choose the Bhayandar branch. Saphale, Palghar and Boisar/Tarapur students attend the Boisar branch (Palghar is about 10–12 minutes from Boisar by train).
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Can I attend a free demo class before joining?
Yes. Fill the enquiry form on this page or call +91 90768 32616. A counsellor will call you back the same day and book a free demo at the branch nearest to you.
Develop practical AI skills for Data Science, analytics, Machine Learning, programming, reporting and business problem-solving. Join the AI course at TIIT Computer Education.
