Who is a Data Science & AI Engineer?
A Python Full Stack & AI Engineer is a multi-skilled professional who develops modern web applications, builds intelligent data-driven systems, and deploys AI-powered solutions in the cloud.
Python Full Stack development focuses on building complete web applications using frontend technologies like HTML, CSS, JavaScript, React and backend frameworks like Django, FastAPI, and Node.js, integrated with databases and cloud infrastructure.
Data Science, Machine Learning, and Deep Learning involve extracting meaningful insights from large datasets, building predictive models, and creating intelligent systems capable of learning from data. These technologies are widely used in business analytics, healthcare, finance, marketing, climate research, and automation.
Generative AI and Agentic AI represent the next generation of artificial intelligence, where systems can generate content, automate tasks, reason, and act autonomously using Large Language Models (LLMs), AI agents, and orchestration frameworks. These technologies are transforming industries including software development, education, customer support, research, and enterprise automation.
LinkedIn and global tech reports list Full Stack Development, Data Science, Machine Learning, and Generative AI as among the fastest-growing job roles worldwide. The global AI market is expected to grow exponentially by 2026, creating millions of new jobs. India has emerged as one of the largest talent hubs for Full Stack and AI professionals with massive demand across startups, IT services, and global enterprises.
Specializing in Python Full Stack, Data Science, Machine Learning, Deep Learning, Generative AI, and Agentic AI gives you a strong head start in the technology industry. Career opportunities include Full Stack Developer, Data Analyst, Machine Learning Engineer, AI Engineer, Generative AI Developer, and AI Agent Engineer with salary ranges in India from 6 LPA to 21 LPA for freshers and experienced professionals, and globally from USD 100,000 to USD 150,000+ per annum.
PROPEL DSE PRO: Python Full Stack Web Development + Data Science Engineering + AI/ML + Generative AI Course Overview
PROPEL DSE PRO with dual specialization in Python Full Stack Development and Data Science Engineering has been designed to meet the requirements of the software industry for Full Stack Python Web Developer and Data Scientists, Data Analysts and Data Engineers . It prepares candidates to begin their career in this exciting field and develop themselves into successful professionals in Software Engineering or Data Science Engineering. The program focuses on holistic development of the participants.
Keeping this in mind, the designers of the program have given a balanced treatment of different areas such as technology, soft skills, language fluency, behavioural orientations and basic business knowledge. The program enables participants to become professionals who solve real-world problems through the medium of Software and Data Science Engineering.
The total duration of the programme is 100 working days, divided into 8 camps. First 4 Camps in Phase 1 focus building the foundation in Programming, Database and Web Development. Camps 5-8 in the phase to builds on the phase 1 to build your skills Data Science. Each Camp has a major objective, and builds over the learning from the previous one. Multiple assignments, Case studies and project in every camp makes the learning immersive, engaging and transformational for the learners.
Course Content
(Click on each Camp to view its details)
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Participants are given an introduction to the course, expectations and goals to be achieved are set , and commit to develop the knowledge, skills and orientations required to achieve them, taking personal responsibility while working in a collaborative environment.
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Understanding Programming Logic
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Understanding Data Types, Keywords, operators and control constructs in Python
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Exception Handling
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Programming in Python using OOPS Concepts
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Create a simple CRM project
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Defining and manipulating Databases using DDL and DML
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Using commands and functions to manipulate data in database
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Use DQL and different clauses- Where, Order By, Group By, Having
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Using joins to view related/ relevant information from different tables
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Use subqueries
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Work with other objects in Databases (Views, Indexes, Sequences)
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Normalisation of Database
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Normalisation workshop
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NOSQL - MongoDB
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HTML, HTML5
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CSS
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Java Script
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Bootstrap and Tailwind
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Responsive Page Design
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Understanding Django Project Structure
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Managing Django URLs
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Django Templates, Models with databases
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Django authentication system
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REST API using Django
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The registration and login feature using JWTs
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Writing the content model
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Nesting routes
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Consume REST API using Javascript+JQuery and Ajax
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Web Application using REST API workshop
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Microservices, Docker and CI-CD Pipeline using AWS
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Numpy, Pandas, Data Visualization using Matplotlib, Seaborn, Bokeh, Plotly
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Probability and Statistics for Machine Learning
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Data Pre Processing, Supervised and Unsupervised Machine Learning Algorithms
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Optimization and Web Scrapping
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Artificial Neural Networks and Convolutional Neural Networks
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Object Recognition and Face Recognition
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Popular Generative AI Models- Case Study with Practicals
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NLP, Transformers and Auto Recursive Models in Depth
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RAG, Fine Tuining, LLM API Implmentation
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Agentic AI Frameworks, Workflow Automation
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Final Capstone Project Development
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Final Capstone Project Presentation