PG Program In Data Science, ML & AI

In collaboration with Microsoft Logo
(Certiport)

Master in data science skills in 12 months with hands-on projects, real-world case studies, and personalized mentorship. Join us to unlock your potential in the rapidly evolving field of data science.

SkillVersed's 4 Step Path for your Guaranteed Success

The Data Analytics course offered by the Skill Versed Institute is developed with insights from industry experts and professionals. SkillVersed’s comprehensive curriculum ensures you gain all the essential analytics skills and expert guidance needed to land your dream job in data analytics.

Mentorship
Career Growth Guarantee

With our guaranteed career support, mentorship, and placement guidance, you’ll have everything you need to start your professional journey in the US with confidence.

01
Curriculum
Industry-Focused Learning

Master the essential tools, languages, and techniques shaping today’s data-driven workplaces.

03
Mentorship session
Projects
Personal Mentorship from Industry Experts

Gain tailored 1:1 guidance and insights from top professionals throughout your learning journey.

02
Support
Applied Learning Through Projects

Gain practical experience by working on 50+ guided projects and case studies drawn from real business environments.

04
Course Curriculum

Learn What Employers Value. Build What They Need.

Our curriculum is shaped by US industry experts and focused on real skills that matter. From tools to techniques, every lesson prepares you for real opportunities ,So you graduate confident, capable, and career-ready.

Basic Excel
Key Areas of Learning
  • Introduction to Excel
  • Fundamentals of Excel
  • Data Exploration with Built-in Functions
  • Basic Visualization Analytics
  • Charts and Graphs
Advanced Excel
Key Areas of Learning
  • Functions
  • Lookup, VLOOKUP, INDEX, HLOOKUP
  • Date and Time Functions
  • Data Tables and Validation
  • Pivot Tables
  • Financial Functions
  • Macros & Coding
  • Custom Formatting and Advanced Filters
Storytelling & Dashboard Creation
Key Areas of Learning
  • Storytelling with Excel
  • Basics of Dashboarding
  • Creating Advanced Dashboards
Basic SQL
Key Areas of Learning
  • Introduction to Databases & Queries
  • Extracting Data using SQl
  • Setting Up Big Queries
  • Function Filtering & Sub-Queries
  • Join Sub Queries
  • Aggregation
  • Date & Time Functions
  • Indexing & Partitioning
Probability & Statistics
Key Areas of Learning
  • Probability
  • Bayes Theorem
  • Distribution
  • Discriptive Statistics & Outliers Treatment
  • Hypothesis Testing & AB Testing
  • ANOVA
  • Correlation
Power BI
Key Areas of Learning
  • Introduction Power BI
  • Cleaning, Transforming, & Loading Data
  • Designing a Data Model
  • Visualisation
  • Introduction to DEX
  • Dashboarding
  • Generating Reports
  • Case Studies
Python Programming
Key Areas of Learning
  • Programming Basics
  • Conditions & Loops
  • Functions
  • String Handling
  • Data Structures
  • OOPs
Data Wrangling
Key Areas of Learning
  • Numpy & Pandas
  • Data Acquisition
  • Web Scraping
  • BeautifulSoup & Selenium
Data Visualization
Key Areas of Learning
  • Matplotlib
  • Seaborn
  • Visualisation using Charts & Graphs
Machine Learning
  • Regression & Classification
  • Decision Trees & Random Forest
  • Clustering & DBSCAN
  • EDA & Feature Engineering
  • Model Building & Tuning
Big Data
Key Areas of Learning
  • Big Data Fundamentals
  • Hive & Data Warehousing
  • Apache Spark
  • AWS Big Data
  • NoSQL Databases
ML Ops
Key Areas of Learning
  • Flask
  • Docker & Containerisation
  • MLflow
  • CI/CD
  • AWS ML Operations
Deep Learning
  • Neural Networks
  • TensorFlow & Keras
  • Forward & Back Propagation
  • Hyperparameter Tuning
  • TensorBoard
Computer Vision
  • CNN Architectures
  • Object Detection & Segmentation
  • GANs
  • Data Augmentation
NLP & Generative AI
  • Text Preprocessing
  • Word Embeddings & Transformers
  • Sentiment Analysis
  • Generative AI & Ethics
  • Capstone Project
  • Git & GitHub

Tools & Technologies Covered

Explore the wide range of tools and technologies you'll master throughout our programs.

Excel
GitHub
GPT
Gradio
Hugging Face
Keras
LangChain
Matplotlib
NumPy
OpenCV
Pandas
Python
R
Scikit-learn
SciPy
Seaborn
spaCy
Tableau
TensorFlow
Tool
Transformers
Testimonials

What Our Students Say

Hear from our students about their learning experiences and successes.

Why Attend

Ready to Elevate Your Skills?

Join Skill Versed today and embark on a transformative learning journey!

Certificate of Completion
Project Completion Certificate
Microsoft Certificate

Start your journey with a simple registration.

Register in a few simple steps—fill in your details, verify your email, and start exploring our services. Fast, secure, and easy!

1
Apply For The Program
2
Qualification Check
3
Enrollment Process
4
Session From Mentor

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Program Fee

Comprehensive training, hands‑on projects, and mentorship in an affordable plan.

LIMITED SEATS

Program Fee

Fee Structure


$ 5,999

Including all tax

Easy pay option with monthly EMIs available
Everything You Need to Know

Frequently Asked Questions

What is the PG in Data Science program?
The PG in Data Science is a professional postgraduate program designed to build strong foundations in data analysis, statistics, and machine learning. The program equips learners with skills in data exploration, predictive modeling, and data-driven decision-making to become job-ready data scientists within 6 months.
Who should enroll in this program?
This program is ideal for graduates, early-career professionals, and career-switchers who want to pursue roles in data science, machine learning, or AI. A basic understanding of mathematics and logical reasoning is helpful, but prior programming experience is not mandatory.
What is the program duration and format?
The program runs for approximately 12 months and follows a blended learning approach with instructor-led live sessions, weekly mentorship, self-paced modules, hands-on labs, and practical assignments. The schedule is designed to balance learning with academic or professional commitments.
Which tools and topics are covered in the curriculum?
Core topics include Python (NumPy, Pandas, Matplotlib, Seaborn), SQL, statistics & probability, exploratory data analysis, machine learning algorithms, data preprocessing, model evaluation, and an introduction to deep learning and AI concepts using real-world datasets.
Are there projects and a capstone?
Yes. Learners work on 50+ hands-on exercises and multiple real-world projects such as predictive analytics, classification models, and recommendation systems. The program culminates in a mentor-guided capstone project demonstrating an end-to-end data science solution.
What placement support and certifications will I receive?
Graduates receive a Certificate of Completion and a Project Completion certificate. The program also provides placement support including resume and portfolio building, technical interview preparation, mock interviews, and employer referrals to help secure data scientist and machine learning roles.