Master the practical application of Data Analytics and AI to convert raw data into powerful insights that fuel strategic business decisions. This 100% Job Assurance program is crafted for fresh graduates and working professionals aiming to build a high-growth career in analytics.
Gain real-world experience with tools like SQL, Python, Power BI, and Excel, and work on industry-grade projects across sectors like finance, retail, and healthcare. Prepare for top roles like Data Analyst, Reporting Analyst, BI Analyst, and more—with end-to-end placement support and career mentorship.
Comprehensive curriculum covering Python, Machine Learning, Deep Learning, NLP, and Big Data technologies.
Get placed in a data science role within 6 months of graduation or receive a full refund of your program fee.
Learn from top industry experts through interactive live sessions with real-time doubt resolution and hands-on guidance.
Personalized guidance from industry mentors to help you navigate your learning journey effectively.
Resume building, interview preparation, and exclusive access to job opportunities with top companies.
Work on real-world projects to build a strong portfolio that showcases your data science expertise.
Our industry-aligned curriculum is designed by experts to help you master the most in-demand data science skills and prepare you for a successful career.
This foundational module sets the tone for your entire Data Science journey. The goal is to ensure that every learner is confident in working with raw data—structuring it, cleaning it, transforming it, and deriving meaningful insights. You’ll begin with spreadsheet tools like Excel and Google Sheets, progress into structured querying with SQL, and learn to work with relational databases. From there, you’ll explore modern data visualization tools like Tableau and Power BI, which are critical for communicating data-driven findings.
Learn the fundamentals of Excel, including formulas, pivot tables, charts, and statistical functions, while exploring dashboards, What-if analysis, and Google Sheets for collaboration and effective team workflows. Read More
Understand the basics of databases, including CRUD operations, joins, aggregations, filtering, subqueries, window functions, and CTEs to query and manage structured data efficiently for real-world analytics. Read More
Build a strong foundation in relational databases such as MySQL and PostgreSQL, learning indexing, normalization, and data modeling concepts to optimize performance and structure for efficient information storage and retrieval. Read More
Learn Power BI and Tableau essentials, including connecting data sources, creating calculated fields, dashboards, KPIs, and applying visual storytelling techniques to communicate actionable insights effectively to stakeholders. Read More
Gain expertise in data wrangling basics, including handling missing values, reshaping datasets, transforming columns, and performing type conversions to prepare clean, analysis-ready datasets suitable for reliable insights and reporting. Read More
This module equips you with hands-on programming skills using Python—the most in-demand language in data analytics. You’ll start with basic programming concepts and gradually advance to working with essential libraries used for manipulating and analyzing data. You’ll also get introduced to best practices like using Jupyter Notebooks for analysis and Git/GitHub for version control and collaboration.
Master Python basics, including variables, data types, conditionals, loops, and functions, to build a foundation for flexible data manipulation, analysis, and automation in business applications. Read More
Learn to work with NumPy arrays and Pandas Series/DataFrames for data cleaning, indexing, and aggregation, transforming raw datasets into structured formats suitable for statistical analysis and visualization tasks. Read More
Create professional visualizations using Matplotlib and Seaborn, including bar charts, histograms, pairplots, and heatmaps to communicate insights effectively through visually appealing, easy-to-interpret graphics. Read More
Organize and execute analysis scripts in Jupyter Notebooks for interactive, reproducible data exploration, allowing you to document workflows and maintain structured, professional analytical projects. Read More
Understand Git and GitHub for version control, including pushing code, pull requests, and repository management to collaborate efficiently on projects and maintain a reliable code history. Read More
In this module, you’ll develop statistical thinking—learning how to use data to make business decisions. From summarizing and interpreting datasets to applying hypothesis tests and probability models, this module focuses on turning raw data into insights that drive real-world strategy and decision-making.
Apply descriptive and inferential statistics to analyze data distributions using mean, median, mode, variance, and sampling techniques, gaining the ability to make informed, data-driven business decisions. Read More
Explore probability and distributions, including normal, binomial, and Poisson distributions, and run simulations to assess uncertainties and model outcomes for predictive analytics applications. Read More
Perform hypothesis testing using t-tests, z-tests, chi-square tests, and confidence intervals, validating business assumptions and ensuring strategies are backed by statistically sound evidence. Read More
Design and evaluate A/B testing experiments to optimize performance in marketing, pricing, and product decisions using structured experimentation methods and measurable outcomes. Read More
Apply statistical tools to business case studies in marketing, operations, and product decision-making, translating analysis into actionable recommendations for real-world challenges. Read More
In this module, you’ll learn to communicate analytical insights using data visualization tools and storytelling frameworks. You’ll build dynamic dashboards, present KPIs, and structure insights in a way that non-technical stakeholders can easily understand.
Prepare data by cleaning missing values, correcting formatting issues, and creating report-ready datasets, ensuring accuracy and consistency for downstream analytics, visualization, and reporting tasks. Read More
Visualize business data using Power BI or Tableau dashboards, applying KPIs and calculated fields, to highlight trends, monitor performance, and communicate insights effectively to stakeholders. Read More
Apply visual storytelling techniques to data to influence business decisions and strategy, crafting narratives that clearly communicate insights and recommendations to executives and teams. Read More
Prepare executive-ready reporting formats, including decks and dashboards, as used by professional analysts in consulting and finance to convey insights effectively to leadership. Read More
Analyze industry-specific datasets from healthcare, retail, BFSI, and e-commerce to extract meaningful insights, applying analytics tools to solve business challenges and optimize operational performance. Read More
Build robust business solutions using Excel and SQL together. This module focuses on real-time analytics applications using industry datasets across sales, operations, and customer data.
Master advanced Excel techniques including IF statements, nested formulas, INDEX/MATCH, data validation, and conditional formatting to handle complex business problems efficiently within Excel. Read More
Build interactive Excel dashboards with slicers, charts, pivot tables, and macros, to present actionable insights and automate repetitive reporting tasks effectively. Read More
Write complex SQL queries using window functions, CASE statements, subqueries, unions, and views to handle intricate business data requirements and extract actionable insights. Read More
Combine datasets across domains using advanced cross-table joins and data modeling techniques, integrating multiple sources to support comprehensive business analysis and reporting. Read More
Work on domain-specific projects solving business problems in retail, BFSI, and e-commerce, applying analytics techniques to real scenarios such as sales tracking, loan approvals, and order analysis. Read More
Apply everything you’ve learned through two major capstone projects and intensive job preparation. This module is designed to polish your profile, build your portfolio, and help you face real interviews with confidence.
Undertake a capstone project focused on Exploratory Data Analysis (EDA), analyzing datasets from scratch using Python and SQL to develop end-to-end analytical skills. Read More
Create a second capstone project comprising a BI dashboard and business presentation, demonstrating the ability to communicate insights effectively through interactive dashboards and executive reports. Read More
Optimize your resume and LinkedIn profile for data-related roles to stand out to recruiters, learning how to professionally present skills, projects, and achievements in a compelling format. Read More
Participate in mock interviews covering technical and HR rounds with real questions, building confidence and readiness to secure analytics roles successfully. Read More
Curate a professional portfolio showcasing completed projects and case studies, preparing for interactions with hiring partners and demonstrating tangible evidence of skills and experience. Read More
Your learning journey is more than just gaining knowledge—it’s about growth, discovery, and transformation.
Learners placed in top global companies across UAE, UK, Canada, and more.
10+ Batches 500+ LearnersEmpowering professionals and freshers to level up through skill-based learning.
110+ Batches 5K+ LearnersTrusted by industry-leading recruiters and top-tier startups.
110+ Batches 5K+ LearnersLearners have reported significant hikes post program completion.
1000+ PlacementsLearn from experienced mentors with proven industry expertise
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Use K-means clustering to segment customers based on demographics and transaction history. Present insights via dashboards for targeted campaign planning.
Build a predictive model to identify telecom customers likely to churn using historical usage and complaint data. Recommend data-driven retention strategies.
Analyze multi-region sales data and create an interactive dashboard to identify top-performing products, regions, and sales reps.
Use historical loan application data to predict likelihood of default and assign risk scores to new applicants for smarter lending decisions.
Analyze SKU-level sales and returns to optimize inventory levels and reduce holding costs across categories. Build a reorder suggestion model.
Analyze patient history and diagnosis codes to identify factors influencing hospital readmissions within 30 days.
Evaluate multi-channel marketing campaign performance and determine the ROI per channel. Provide recommendations for future budget allocation.
Develop a machine learning model to predict employee attrition based on HR data such as tenure, job satisfaction, and appraisals.
Dedicated career support to transform your skills into a successful data science career.
Real stories of career transformations with our Data Analytics program.