Skill Expresso
HomePrograms › Data Science

Postgraduate Program in Data Science

A hands-on journey through the full data science pipeline — from Python and statistics to machine learning, deployment and MLOps.

Live + LMS delivery100+ hours3 days a week or weekendsCapstone readyML and AI focused
500+Hiring companies
60%Average salary hike
60 LPAHighest salary
1:1Career coaching

Outcomes

What you will learn

Data science drives innovation across every industry. This program equips you with real-world tools, machine learning techniques and business-ready skills.

Build a rock-solid Python foundation — data structures, OOP, NumPy and Pandas
Master the data science lifecycle: wrangling, EDA, statistics and visualization
Train, evaluate and tune machine learning models — regression, classification, clustering
Go advanced with ensembles, NLP, time-series forecasting, XGBoost and LightGBM
Deploy models with Streamlit and Flask, and learn MLOps and explainable AI practices
Deliver a full capstone: a deployed, evaluated model framed in real business context

Career Outcomes

Roles this program prepares you for

Build a profile that maps to the roles hiring teams are actively recruiting for.

Data ScientistMachine Learning EngineerData AnalystAI EngineerData EngineerComputer Vision SpecialistBig Data ScientistBI ScientistResearch Scientist — AI/MLNLP EngineerPrincipal Data ScientistHead of Data Science

Curriculum

8 modules, from fundamentals to mastery

Every module blends live teaching, practice and feedback — open each one to see exactly what you will cover.

01

Master the Basics of Programming

A hands-on introduction to programming: essential concepts, key data structures like lists and dictionaries, and your first steps into Object-Oriented Programming.

  • Gain hands-on coding skills in Python
  • Write clean, efficient code using real-world examples
  • Understand data structures and OOP fundamentals

Basics

Syntax and StructureVariables and Data TypesConditional LogicLoops and IterationsFunctions and ReuseLists and Dictionaries

Advanced

Object-Oriented ProgrammingError HandlingLambda and MapModules and PackagesList ComprehensionAPI Integration
02

Excel and Statistics Foundation

Organise, format and analyse data efficiently while building the statistical intuition every data scientist needs.

  • Master Excel essentials for data entry, formatting and analysis
  • Automate calculations with formulas and functions
  • Create clean, professional spreadsheets and visual reports

Basics

Excel Interface and ShortcutsCommon Formulas and FunctionsData Entry and FormattingCharts and GraphsSorting and FilteringPivot Table Essentials

Advanced

VLOOKUP, XLOOKUP and INDEX-MATCHAdvanced Pivot Table DesignConditional Formatting RulesData Validation and Clean-UpPower Query for ETLInteractive Dashboard Creation
03

Python for Data Science

Develop essential programming skills: write, structure and debug code, explore core data structures and get a solid grounding in OOP for data work.

  • Develop practical programming skills for data science
  • Write clean, efficient and functional Python code
  • Understand core logic, data structures and OOP fundamentals

Basics

Core Python SyntaxData Types and VariablesConditional Logic and LoopsFunctions and ParametersLists and DictionariesFile I/O Operations

Advanced

NumPy Arrays and MathDataFrames with PandasList Comprehension and LambdaException HandlingObject-Oriented ProgrammingModules, Packages and Scripts
04

Data Science Core

The heart of the discipline: the data science lifecycle, wrangling with Pandas, exploratory analysis, statistical foundations and visualization.

  • Work the full data science lifecycle on real datasets
  • Wrangle, explore and visualize data with confidence
  • Build statistical foundations for sound modelling

Basics

Data Science LifecyclePython for AnalyticsData Wrangling with PandasExploratory Data AnalysisStatistical FoundationsData Visualization

Advanced

Feature EngineeringRegression and ClassificationClustering and PCAModel Evaluation MetricsEnsemble Techniques — XGBoostModel Deployment Tools
05

Machine Learning

Build, evaluate and explain complex models — then go beyond model-building into ML engineering: pipelines, monitoring, drift and scalable, ethical deployment.

  • Master advanced machine learning algorithms
  • Evaluate and tune models for better performance
  • Design, build and deploy scalable ML pipelines
  • Apply explainable AI and MLOps practices for real-world implementation

Basics

What is Machine Learning?Regression and Classification ModelsClustering and Dimensionality ReductionFeature Engineering TechniquesModel Training and TestingAccuracy, Precision, Recall

Advanced

Hyperparameter Tuning — GridSearch, RandomSearchEnsemble Learning — Random Forest, BoostingNatural Language ProcessingTime Series ForecastingXGBoost and LightGBM ModelsDeployment with Streamlit and Flask
06

Capstone Project

Choose a real-world business problem, apply your Python, ML and AI knowledge to build and evaluate models, then tune and deploy them into production.

  • Apply end-to-end data science skills to a real scenario
  • Build and deploy a complete model using ML and AI skills

Capstone Journey

Classification ModelingFeature SelectionModel Evaluation — AUC, Confusion MatrixBusiness Context FramingModel Deployment
07

Art of Storytelling

Transform data into compelling stories that influence decisions — craft narratives with clarity, structure and visual impact.

  • Present data-driven insights with confidence
  • Craft impactful narratives from analysis
  • Influence decisions through visuals and story flow

Storytelling Skills

Audience UnderstandingInsight FramingVisual EncodingNarrative FlowData-to-DecisionPresentation Impact
08

Career Support

Transition from learning to earning: craft a standout resume, build a professional portfolio and prepare for interviews in data-centric roles.

  • Build a compelling, industry-aligned resume and LinkedIn profile
  • Practice interview scenarios with mock sessions and feedback
  • Articulate your data skills and project work confidently

Career Toolkit

Resume EnhancementLinkedIn OptimizationMock InterviewsJob Opportunity AccessPortfolio ReviewInterview Readiness

Portfolio

Hands-on projects you will build

Real datasets, real business questions — every project becomes part of your professional portfolio.

EdTech Learner Dashboard

Track student progress, engagement and quiz outcomes with an interactive dashboard that improves retention.

Retail Sustainability Tracker

Analyze eco-friendly product performance across regions using sales trends and margin insights.

Heart Disease Predictor

Build a classification model assessing heart-disease risk from patient history, with feature analysis of key contributors.

Smart Energy Forecasting

Use time-series modelling to forecast daily energy usage on a smart campus and recommend efficiency strategies.

Vaccine Demand Prediction

Forecast vaccine requirements from regional trends and mobility data using time-series models.

Ethical Brand Sentiment Classifier

Classify customer reviews of ethical brands and use explainable AI to uncover sentiment drivers.

Resume Screening with NLP

Train a model to assess resume-job fit using keyword extraction and classification.

City Traffic Congestion Forecasting

Predict congestion across city routes from traffic, weather and time data — supporting smart-city planning.

Career Services

Support that goes beyond the classroom

A dedicated career advisor works with you from first class to final interview.

1:1 Career Mentoring

Personalised guidance on your goals, gaps and the fastest path to your target role.

Resume and Profile Building

A resume that works, plus LinkedIn and GitHub profiles that reflect your skills credibly.

Mock Interviews

Practice real interview scenarios with expert feedback until you walk in confident.

Job Opportunity Access

Curated openings aligned to your skill set, with guidance on positioning your profile.

Eligibility

Who is this program for?

Fresh Graduates and Postgraduates

Individuals with at least 50% marks in graduation, seeking a strong launchpad into the data industry.

Working Professionals (0–8 Years)

Early- to mid-career professionals looking for a career transition, skill upgrade or salary growth in data-driven roles.

Evaluation

How you are evaluated

Assessment is continuous and practical — you always know where you stand and what to improve next.

01

Module Quizzes

Every module ends with a 10-question quiz. Score 70% to pass, with unlimited retakes and explanations for every answer.

02

Hands-on Assignments

Practical labs after each module, reviewed with mentor feedback so skills stick beyond theory.

03

Capstone Evaluation

Your capstone is evaluated by faculty on approach, execution and a stakeholder-style final presentation.

04

Final Assessment

A comprehensive overall quiz spanning all modules — 50 questions, 70% to pass — confirms you are certification-ready.

Certificate criteria: complete all modules and assignments, pass every module quiz, clear the final assessment, and present your capstone project.

Try It

Sample quiz — test your instincts

A taste of the module quizzes inside the program. Click an answer to check yourself — instant feedback, no signup needed.

Q1. Which metric setup is most appropriate for an imbalanced classification problem?

Accuracy alone
Precision and recall
R-squared
Mean absolute error

With rare positives, accuracy misleads — precision and recall reveal how well the model finds the minority class.

Q2. We split data into train and test sets to…

Speed up training
Measure how the model generalises to unseen data
Clean missing values
Reduce feature count

Held-out test data estimates real-world performance and exposes overfitting.

Q3. Which of these is an ensemble method?

K-Means
XGBoost
PCA
Linear Regression

XGBoost combines many weak tree learners through boosting into one strong predictor.

Q4. Feature engineering means…

Tuning hyperparameters
Creating better input variables from raw data
Deploying models to production
Labelling training data

Well-crafted features — ratios, encodings, aggregates — often improve models more than algorithm choice.

Q5. Streamlit is typically used to…

Train deep learning models
Build interactive data apps and model demos
Store large datasets
Version control code

Streamlit turns Python scripts into shareable web apps — the fastest path from model to demo.

🎓

Certification

Postgraduate Certificate in Data Science

An industry-recognised credential from Skill Expresso Edu Solutions that enhances your professional profile and accelerates your career growth.

Admissions

A simple, guided admission process

Submit Application

Complete the online application form with your basic details and background.

Profile Review

Our admissions team evaluates your academic and professional suitability.

Counselling Call

A one-on-one discussion to clarify goals, learning path and expectations.

Confirmation

Receive your confirmation of selection and payment instructions.

Enrolment

Complete payment, receive LMS access and begin your learning journey.

Ready to move your career forward?

Talk to a counsellor, get your questions answered, and find out if this program is the right fit — no pressure, no obligation.

Apply Now ↗Book Free Counselling
© 2026 Skill Expresso Edu SolutionsPrivacy PolicyTermsRefundsDesigned by elevana.guru
Scroll to Top
call us