Data Science Course Outline With Generative AI: PW Skills

Get a complete data science course outline to start your data science journey with PW Skills. Get complete course details about the important modules covered within the course like Python, Machine Learning, Deep Learning, Generative AI, NLP, etc.
authorImageVarun Saharawat30 Oct, 2025
Data Science Course Outline With Generative AI: PW Skills

Get an extensive data science course outline offered by PW Skills and become a certified data scientist this season. The complete syllabus is based on the latest industry curriculum to help students grab the best offer in the market. 

Utilise the power of Generative AI tools and technologies within this course. In this article, let us get complete details on the data science course outline of PW Skills Data Science with Generative AI Course.

Become a Certified Data Scientist with PW Skills

Learn top-in-demand data scientist skills with PW Skills Data Science Course. Enrol in this job assistance Data Science Program and discover a wide range of career opportunities in the field of data science. 
Name of the course  Data Science with Generative AI Course
Duration 6 Months
Program Job Assistance Program
Delivery Mode Live + Recorded
Language English
Real World Project 4+ Capstone Projects 
Interview Opportunities  Yes
Certification Yes

Data Science Course Outline 

Let us quickly get to the data science course outline and discover the curriculum of the course below.

Module 1: Python Basics

Module 2: Data Types & Functions

  • Data Structure in Python
  • Strings Object basics
  • Inbuilt Methods
  • Splitting Inbuilt Methods
  • List Methods
  • List Comprehension
  • Dictionary
  • Function Basics
  • Generator Functions 
  • Lambda Functions
  • Map, Reduce, Filter Functions

Module 3: OOPs

Files & Exceptional Handling 

  • Working With Files
  • Reading And Writing Files
  • Buffered Read And Write
  • Other File Methods.
  • Logging, Debugger
  • Modules And Import Statements
  • Exceptions Handling With Try-Except
  • Custom Exception Handling
  • List Of General Use Exception
  • Best Practice Exception Handling

Database & Web API

  • Multithreading
  • Multiprocessing
  • Mysql
  • Mongo Db
  • What Is Web Api
  • Difference B/W Api And Web Api
  • Rest And Soap Architecture
  • Restful Services

1. Python Module

This module in the Data Science Course outline consists of three important subparts that will help you learn Python language from scratch

Python Basics 

In this module, you will learn about Basic python programming, data structure, and OOP concepts.

Advance Python

Here you will learn concepts like handling errors and exceptions in Python, logging event details with python modules

Database and Web API

Learn how to create web API, and DBMS like MySQL, and MongoDB. Create API connections using Python. Get a basic understanding of web application architecture.

Statistics Basics 

  • Introduction To Basic Statistics Terms
  • Types Of Statistics
  • Types Of Data
  • Levels Of Measurement
  • Measures Of Central Tendency
  • Measures Of Dispersion
  • Random Variables
  • Set
  • Skewness
  • Covariance And Correlation

Statistics Advance

  • Probability Density/Distribution Function
  • Types Of The Probability Distribution
  • Binomial Distribution
  • Poisson Distribution
  • Normal Distribution (Gaussian Distribution)
  • Probability Density Function And Mass Function
  • Cumulative Density Function
  • Examples Of Normal Distribution
  • Bernoulli Distribution
  • Uniform Distribution
  • Z Stats

2. Statistics 

Get familiar with the statistics concepts in this module and know the impact of statistics behind any business to be implemented.

Basics in Statistics

In this module get familiar with statistical concepts.

Advance Statistics

Get familiar with the advanced concepts of statistics and its impact in any business.

3. Machine Learning 

Get familiar with machine learning models and algorithms in this module. Learn about feature engineering and Data analysis with important key parameters. The machine learning module is divided into eight distinct parts.
  • Module 1: Introduction to ML
  • Module 2: Feature Engineering
  • Module 3: Exploratory Data Analysis
  • Module 4: Regression
  • Module 5: Decision Trees & SVM
  • Module 6: Naive Bayes & Ensemble Techniques
  • Module 7: Boosting, KNN & Dimension Reduction
  • Module 8: Anomaly Detection & Time Series

Introduction

Get familiar with fundamental terminologies in the Data Science course outline.

Feature Engineering 

Get familiar with how statistics make an impact behind any business idea to be implemented.

Exploratory Data Analysis

Learn to use statistics to explore data and find important insights from the data to monitor key parameters.

Machine Learning Algorithms

  • Regression Models
  • SVM 
  • Clustering Algorithms
  • Decision Trees
  • Bagging and Boosting Techniques

Projects

There are advanced projects related to the course using ML Models and deploying it on the cloud platforms. 
  • Spam detection
  • Climate Visibility

4. Deep Learning

Learn the concept of building neural networks in the data science domain. Learn how to use deep learning libraries like TensorFlow and PyTorch.
  • Neural Network
  • Tensorflow
  • PyTorch & CNN
  • Image Classifications
  • RCNN, YOLO, Detectron2 & TFOD2
  • Image Segmentation & Mask Rcnn
  • Object Detection
  • GAN

Artificial Neural Network (ANN)

Learn how to build neural networks and their impact on the data science domain. Learn demanding libraries of deep learning like Pytorch and Tensorflow within this module.

Convolutional Neural Networking (CNN)

This part provides CNN Models from scratch where you can learn how to create CNN Models and use it in image classification, object classification, and many more applications in the various industries.

Real World Projects

There are two important projects covered in the data science course outline which is Mini project using Tensorflow and Face detection project.

5. Natural Language Processing (NLP)

Learn how to prepare textual data output from NLP and the basics of RNN and other advanced models using NLP. With NLP, devices can easily recognize, understand, and generate text-like responses based on a rule-based machine language inspired by NLP. PW Skills Data Science course covers text processing, NLP libraries, models, and more.
  • Module 1: Introduction of NLP
  • Module 2: Text Processing using NLP
  • Module 3: NLP Libraries 
  • Module 4: NLP Models
  • Module 5: Transfer Learning 

6. Generative AI Module

The most in-demand module in the data science course outline is the utilization of generative AI. Learn current in demand AI tools and techniques used in the industry to analyze and synthesize data. 
  • Hugging Face
  • LLMs
  • BERT
  • GPT
  • Image generator 

Project

Cover innovative projects on how to build a chatbot from scratch using Langchain and Chainlit AI tools. It not only responds to textual queries but can also generate a visual representation of the output.

7. Power BI

Master Data Analytic Tools Power BI, which comes optional with the course. This tool is very helpful in making productive data visualization from raw data into interactive insights.

Data Science Course Outline: Real-World Projects 

Build innovative real world projects within the data science course offered by PW Skills. Check the projects in the data science course outline below.

GenAi: An Alexa Like Assistant  (Generative AI Project)

Build an AI assistant with chat and voice command which is useful for executing daily tasks such as web searching, knowledge extractions or providing personalized recommendations.

Customized Chat Bot ( Generative AI Project)

Build a Chatbot using the Long Chain and Chainlit framework which is capable of generating a question-answer system or RAG system that can extract important information from various sources of documents.

Named Entity Recognition ( Generative AI)

Utilise advanced AI transformer models to build a Name entity recognition project that can currently identify and extract any entities from a text document.

On Prompt Image and Caption Generator (Prompt Engineering)

This image generation tool capable of creating captions will help users generate content thumbnails easily. 
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Data Science Course Outline FAQs

Q1. What is the duration of the PW Skills Data Science Course?

Ans: The data science course outline is scheduled to be covered within 6 months.

Q2. What is the delivery mode of the Course online?

Ans: You can learn through live lectures or watch recorded videos at your own scheduled time within the course.

Q3. Are there real world projects in the PW Skills Course?

Ans: Yes, there are over 4+ data science projects within this course based on Generative AI models.

Q4. Where can I enrol in Data Science with Generative AI Course?

Ans: You can easily enrol on the official website of PW Skills in the Data SCience with Generative AI Course.