The Certificate Program in Data Analytics with AI Tools is a comprehensive, industry-focused course designed to help learners master data-driven decision-making using modern AI and data analytics technologies.
This program blends the power of Data Analysis, Machine Learning, and Artificial Intelligence to equip students with the practical skills required in today’s data-centric business world.
From exploring data visualization techniques to building AI-powered dashboards, you’ll gain hands-on experience with tools widely used across industries — including Python, Python Libraries, PySpark to handle Big Data, Power BI, Tableau and other AI automation tools. The course follows a project-based approach, ensuring that you not only understand theoretical concepts but also apply them in real-world business scenarios.
By the end of this data analytics certification, you’ll be able to process large datasets, extract actionable insights, and use AI-driven analytics to predict outcomes and improve decision-making efficiency.
- Must hold a graduate degree in any discipline.
- Basic computer literacy and basic proficiency in English are required.
- No prior experience in data analytics or programming is necessary.
- A laptop or desktop with a stable internet connection.
- Enthusiasm to learn data analytics and AI applications through guided projects.
- Familiarity with Excel or basic statistics is an added advantage(Not Mandatory).
- Commitment to complete all live sessions, assignments, and real-time projects.
- Students and Fresh Graduates aspiring to enter the data analytics or business intelligence domain.
- Working professionals seeking to upgrade their skills for career advancement in data domain.
- Entrepreneurs and decision-makers looking to use AI-powered insights to drive business growth.
Whether you’re a beginner or looking for career transition or domain change, this course ensures you gain both technical expertise and strategic understanding to thrive in the field of data analytics and AI.
What You’ll Get?
Attend interactive live classes led by industry experts and never miss a session with access to high-quality recordings. Learn at your own pace while revisiting key concepts anytime, ensuring a complete and flexible learning experience.
Work on real-world projects under the mentorship of experienced professionals. Learn to implement Agile methodology, collaborate in sprints, and apply practical solutions — building skills that employers value and boosting your confidence to handle real industry challenges.
Our dedicated placement support ensures you never stop until you secure your dream job. From interview prep to company shortlisting, we guide you every step of the way, giving you the tools and confidence to succeed in the competitive job market.
Craft a professional, standout resume with personalized guidance from experts. Learn how to highlight your skills, projects, and achievements effectively — increasing your chances of catching recruiters’ attention without much stress and landing interviews.
Practice with mock interviews designed to simulate real industry scenarios. Receive constructive feedback and gain confidence, then get opportunities to attend live interviews with top companies — ensuring you’re fully prepared to excel.
Get unlimited access to all course materials, including notes, recordings, and resources. Revisit lessons anytime, stay updated with new content, and continue learning even after completing your course.
Join a vibrant community of learners, mentors, and industry experts. Collaborate, share knowledge, seek guidance, and grow together — because learning is better when it’s supported by a strong, like-minded network.
Absolutely! Our tech programs for beginners are designed for learners from all backgrounds — even if you have zero technical experience. We start with the fundamentals and gradually build your skills through hands-on projects and mentorship. Many of our successful learners come from non-technical fields like commerce, arts, and management. By the end of the course, you’ll gain industry-ready skills and a job-ready certification that opens doors to top tech roles.
Yes, definitely! A career gap doesn’t define your future — your skills do. Our training is 100% industry-aligned, helping you gain the latest tools, technologies, and certifications that companies are actively seeking. You’ll also receive dedicated career support — resume building, mock interviews, and placement guidance — to confidently re-enter the workforce with a strong profile and competitive salary.This ensures you can compete for high-paying tech jobs in India and globally, despite a career break.
We believe in complete transparency and learner satisfaction. If you’re not satisfied with the course within the first 7 days of enrollment, you can request a full refund — no questions asked. Beyond that, you can switch to another job-ready course or future batch that better suits your learning goals.
Our learners typically start with packages ranging from ₹4 LPA to ₹8 LPA, depending on the course and skill level. Advanced tracks like AI, Data Analytics, and Cloud Computing can lead to even higher salaries. Completing a job-ready certification from our program enhances your profile and helps you secure high-paying tech jobs in India.
Yes! Once you enroll, you get lifetime access to course materials and session replays. You can revisit the sessions, refresh your skills, and attend future batches at no extra cost. Continuous learning ensures you stay ahead in your career and fully leverage your career gap courses to re-enter the tech industry confidently.
Unlock the power of data with our comprehensive Data Analytics program designed for beginners and professionals alike. This course takes you from the fundamentals to advanced analytics techniques, ensuring you develop the skills to extract actionable insights from real-world datasets.
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Module 1: Python
Dive into the world of Python, the most versatile and beginner-friendly programming language. Perfect for beginners and non-tech professionals aiming to build a strong foundation.
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Lecture 1.1: Introduction to Python and Its Advantages
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Lecture 1.2: Introduction To IDEs
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Lecture 1.3: Why Python ?
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Lecture 1.4: Variable And Its Rules
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Lecture 1.5: Operators
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Lecture 1.6: Data Types
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Lecture 1.7: Conditional Statements and Loops
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Lecture 1.8: Functions And Parameters
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Lecture 1.9: Exception Handling and File Handling
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Lecture 1.10: Regular Expressions
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Lecture 1.11: Numpy
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Lecture 1.12: Pandas
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Lecture 1.13: Matplotlib
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Lecture 1.14: Seaborn
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Module 2: Statistics
Master the fundamentals of statistics to analyze and interpret data effectively. Learn essential concepts and techniques that form the backbone of data-driven decision-making.
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Lecture 2.1: Introduction To Statistics
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Lecture 2.2: Data Collection, Data Preparation and Inference
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Lecture 2.3: Sampling, Types Of Sampling and Variance in sample
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Lecture 2.4: Data Types
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Lecture 2.5: Descriptive Statistics
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Lecture 2.6: Data Distributions
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Lecture 2.7: Probability Theory
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Lecture 2.8: Central Limit Theorem
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Lecture 2.9: Confidence Interval
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Lecture 2.10: Hypothesis Testing
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Lecture 2.11: Correlation and Covariance
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Lecture 2.12: Data Preparation
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Module 3: Stuctured Query Language(SQL)
Master the essentials of SQL to efficiently manage and query databases. Learn to extract, analyze, and manipulate data to make informed, data-driven decisions.
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Lecture 3.1: Introduction to Database
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Lecture 3.2: Understanding The Architecture of the Database
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Lecture 3.3: Data Types In SQL
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Lecture 3.4: Command Types in SQL
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Lecture 3.5: Operators in SQL
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Lecture 3.6: Constraints in SQL
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Lecture 3.7: Joins
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Lecture 3.8: Sub Queries
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Lecture 3.9: Index, Views and Union
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Lecture 3.10: Common Table Expression
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Lecture 3.11: Window Functions
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Lecture 3.12: Triggers
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Module 4: Power BI
Master Power BI to transform raw data into interactive dashboards and insightful visualizations. Gain hands-on experience building real-world reports that drive smart business decisions.
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Lecture 4.1: Prepare The Data
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Lecture 4.2: Get Or Connect To Data
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Lecture 4.3: Profile and Clean The Data
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Lecture 4.4: Transform and Load The Data
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Lecture 4.5: Model The Data
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Lecture 4.6: Design And Implement The Data Model
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Lecture 4.7: Create Model Calculation Using Data Model
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Lecture 4.8: Optimize Model Performance
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Lecture 4.9: Visualize And Analyze The Data
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Lecture 4.10: Enhance Reports For Usability And Storytelling
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Lecture 4.11: Identify Patterns And Trends
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Lecture 4.12: Manage And Secure Power BI
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Lecture 4.13: Create And Manage Workspaces and Assets
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Lecture 4.14: Secure and Govern Power BI Items
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Module 5: Tableau
Master the art of visual storytelling with Tableau and turn complex data into insightful, interactive dashboards.
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Lecture 5.1: Introduction to Tableau
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Lecture 5.2: Tableau Workflow
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Lecture 5.3: Connection and Data Source Setup
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Lecture 5.4: Understand Changes to Data
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Lecture 5.5: Data Simplification and Sorting
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Lecture 5.6: Data Organization
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Lecture 5.7: Specific Values
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Lecture 5.8: Generate Grand Totals, Subtotals, and Changing Aggregation
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Lecture 5.9: Build Highlight Tables
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Lecture 5.10: Data by Date
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Lecture 5.11: Multiple Measures in a View
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Lecture 5.12: Measure Values and Names
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Lecture 5.13: Relationships Between Numerical Values
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Lecture 5.14: Geographic Data Mapping
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Lecture 5.15: Data Customization
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Lecture 5.16: Quick Table Calculations
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Lecture 5.17: View Sharing
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Module 6: Advanced Excel
Unlock the full potential of Excel with advanced formulas, pivot tables, and automation techniques.
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Lecture 6.1: Introduction to Excel & Interface Overview
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Lecture 6.2: Data Entry, Formatting, and Validation
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Lecture 6.3: Formulas & Basic Functions (SUM, AVERAGE, COUNT, etc.)
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Lecture 6.4: Advanced Functions (VLOOKUP, HLOOKUP, INDEX, MATCH)
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Lecture 6.5: Logical Functions (IF, AND, OR, Nested IF)
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Lecture 6.6: Text Functions (LEFT, RIGHT, MID, CONCATENATE, TEXT)
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Lecture 6.7: Date & Time Functions (TODAY, NOW, DATE, YEAR, MONTH)
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Lecture 6.8: Data Sorting, Filtering & Custom Views
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Lecture 6.9: Conditional Formatting & Highlighting Data
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Lecture 6.10: Data Validation & Drop-Down Lists
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Lecture 6.11: Pivot Tables & Pivot Charts
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Lecture 6.12: Charts & Visualizations (Column, Line, Pie, Combo)
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Lecture 6.13: Advanced Data Analysis with Power Query
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Lecture 6.14: Advanced Data Analysis with Power Pivot & DAX
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Lecture 6.15: Scenario Analysis, Goal Seek, and What-If Analysis
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Lecture 6.16: Macros & Introduction to VBA for Automation
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Lecture 6.17: Best Practices in Excel for Data Cleaning and Reporting
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Module 7: PySpark
Learn to process massive datasets efficiently using PySpark and unlock the power of distributed computing
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Lecture 7.1: Introduction to PySpark & Spark Ecosystem Overview
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Lecture 7.2: RDDs (Resilient Distributed Datasets) Basics and Operations
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Lecture 7.3: DataFrames & Spark SQL Fundamentals
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Lecture 7.4: Transformations & Actions in PySpark
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Lecture 7.5: Handling Structured & Semi-Structured Data (CSV, JSON, Parquet)
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Lecture 7.6: PySpark Functions (UDFs, Built-in Functions, Aggregations)
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Lecture 7.7: Data Cleaning & Preprocessing with PySpark
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Lecture 7.8: Joins, Unions, and Merging DataFrames
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Lecture 7.9: GroupBy, Aggregations, and Window Functions
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Lecture 7.10: Working with Spark Streaming & Real-Time Data
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Lecture 7.11: Machine Learning with PySpark MLlib
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Lecture 7.12: Performance Tuning & Optimization (Caching, Partitioning)
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Lecture 7.13: PySpark GraphFrames for Graph Analytics
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Lecture 7.14: Best Practices for Big Data Processing in PySpark
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Module 8: Cloud Analytics
Explore cloud-based analytics platforms to analyze and visualize data from anywhere, anytime. Learn to leverage scalable cloud solutions for faster and smarter business decisions.
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Lecture 8.1: Introduction to Cloud Computing and Cloud Analytics
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Lecture 8.2: Overview of AWS Cloud Services for Analytics
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Lecture 8.3: Overview of GCP Services for Big Data & Analytics
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Lecture 8.4: Overview of Azure Cloud Services for Analytics
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Lecture 8.5: Working with Cloud Storage: S3, GCS, Azure Blob Storage
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Lecture 8.6: Data Ingestion & ETL in Cloud Analytics Platforms
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Lecture 8.7: Introduction to Cloud-based Databases: RDS, BigQuery, Azure SQL
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Lecture 8.8: Basics of Cloud Data Warehousing: Redshift, BigQuery, Synapse
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Lecture 8.9: Cloud-based Analytics Tools: QuickSight, Data Studio, Power BI on Cloud
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Lecture 8.10: Introduction to Cloud Security & Access Management
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Lecture 8.11: Monitoring and Optimization of Cloud Analytics Workloads
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Lecture 8.12: Best Practices for Cloud Data Analytics Projects
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Module 9: Prompt Engieering
Apply your learning in a real-world project to solve business challenges using analytics and AI tools. Showcase your skills to potential employers with a fully functional project.
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Lecture 9.1: Introduction to Prompt Engineering and its Role in Data Analytics
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Lecture 9.2: Understanding Large Language Models (LLMs) like GPT and Gemini
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Lecture 9.3: Types of Prompts – Zero-Shot, One-Shot, and Few-Shot Learning
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Lecture 9.4: Crafting Effective Prompts for Data Exploration and Insights
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Lecture 9.5: Techniques to Improve Model Responses: Role, Context, and Constraints
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Lecture 9.6: Chain-of-Thought and Step-by-Step Reasoning Prompts
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Lecture 9.7: Prompt Templates for Data Cleaning, Summarization, and Insights Extraction
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Lecture 9.8: Prompt Engineering for SQL Query Generation and Automation
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Lecture 9.9: Evaluating and Refining Prompts for Accuracy and Relevance
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Lecture 9.10: Integrating Prompt Engineering with Big Data Tools and Workflows
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Lecture 9.11: Ethical Considerations and Bias Awareness in Prompt Design
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Lecture 9.12: Hands-on Practice: Building Custom Prompts for Analytical Tasks
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Module 10: Capstone Project
Apply your learning in a real-world project to solve business challenges using analytics and AI tools. Showcase your skills to potential employers with a fully functional project.
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Module 11: Live Project
Work on live datasets under expert guidance to gain industry-ready experience. Build confidence by implementing end-to-end solutions that mirror real business scenarios.
Hi! I’m Sai Keerthi, an Analyst at Deloitte with a passion for transforming data into meaningful business insights. I specialize in helping learners bridge the gap between theory and real-world analytics. My sessions focus on practical applications, structured problem-solving, and developing the mindset needed to excel in today’s data-driven industry.
The course content is extremely well-structured and practical. I went from having zero knowledge to confidently working with real-world datasets. The mentors are super supportive and explain every concept clearly!
I loved how interactive and hands-on the learning experience was! The live projects and case studies really helped me understand how data analytics works in the industry. Highly recommend it to anyone starting out in data analytics!
The trainers have deep industry knowledge and make even complex topics feel simple. The course gave me confidence to apply for data analyst roles and even build my own mini projects. Truly worth every minute!