Generative AI Course for Freshers
AI & Machine Learning - Deep Learning & Transformers - RAG & Agentic AI - Fine-Tuning & AIOps - LLMOps - MCP - A2A - LLMs
Quality Thought’s generative AI course for freshers is designed for final-year students and beginners who want to build practical skills in Python, Generative AI, LLMs, RAG, agentic AI, and real-world AI application development. The program combines structured learning with hands-on projects and practical engineering concepts. Explore More Courses from Quality Thought to find additional career-focused training programs.
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Batch Details & Schedule
Choose a learning format and schedule that fits your lifestyle
Course Features & Highlights
Everything you need to build practical Generative AI development skills
Live Projects
Work on real-world projects from day one with industry use cases
Expert Trainers
Learn from industry professionals with 10+ years of experience
100% Placement Support
Dedicated placement cell with assistance until you get hired
Industry Certification
Get certified & boost your resume with recognized credentials
LMS Access
Access to learning materials and recorded sessions
Mock Interviews
Weekly mock interviews to prepare you for real job scenarios
Resume Building
Professional resume preparation and LinkedIn profile optimization
Soft Skills Training
Communication, aptitude, and personality development sessions
Additional Benefits
● Pay After Placement Options Available
● Flexible Payment Plans
● 6-12 Months LMS Access
● Doubt Clearing Sessions
● Mega Job Drives
● 24/7 Learning Support
Your Path to Mastery
Comprehensive training designed to accelerate your career
Exclusive Training
- Training by Industry practitioners
- Capstone projects
- LMS access for 6 months
- Course completion certificate from Quality Thought
- Daily doubt clarification sessions
- Resume building session
- Linkedin & Github guidance
- Interview questions preparation
- 1 mock interview
- Placement referral support
- Course Fee: ₹60,000
Prerequisites & Eligibility
Everything you need to know before enrolling in our Gen AI Developer Program
- Course Prerequisites
- Basic understanding of programming concepts with familiarity with software development being helpful
- Interest in Generative AI, LLMs, RAG, and Agentic AI systems
- Willingness to learn Python, FastAPI, APIs, & AI application development
- Interest in building and deploying AI systems using cloud platforms and modern development practices
Complete Course Curriculum
Comprehensive modules covering every aspect of Generative AI development
Foundations of AI & Machine Learning
- AI & ML Overview: Definitions, Enterprise Use Cases, Emerging Roles
- ML Workflow & Best Practices: Data Ingestion, Feature Engineering, Model Validation
- Python Data Stack: NumPy, Pandas, Matplotlib/Seaborn, Git & GitHub
- Hands-on Lab: Basic ML Classification Project
Deep Learning & Neural Networks
- Neural Network Essentials: Perceptron, Forward/Backward Propagation, Activation Functions
- Hands-On Frameworks: PyTorch & TensorFlow Basics
- CNNs & RNNs: Image Tasks with CNNs, Sequence Data with RNNs/LSTMs
- Hands-on Lab: Training a CNN on MNIST/CIFAR-10
Transformer & Large Language Models (LLMs)
- Transformer Architecture: Self-Attention, Multi-Head Attention, Positional Embeddings
- LLM Ecosystem: OpenAI GPT, Google Gemini, Meta LLaMA
- Prompt Engineering & Fine-Tuning: Few-Shot, Chain-of-Thought, LoRA, Adapters
- Hands-on Lab: Prompt Engineering & Intro to Fine-Tuning
Retrieval-Augmented Generation (RAG)
RAG Fundamentals: Document Chunking, Indexing, Retrieval, Generation
Vector Databases & Embeddings: Pinecone, Chroma, Weaviate, Milvus
Implementing RAG Pipelines with LangChain
Hands-on Lab: Building a RAG Q&A System
Agentic AI Workflows
- AI Agent Concepts: Autonomy, Multi-Step Reasoning, Planning
- Agent Frameworks: LangChain Agents, Semantic Kernel, Crew AI
- Tool & API Orchestration
- Hands-on Lab: Building a Simple AI Agent
Fine-Tuning & Benchmarking Domain-Specific Models
- Advanced Fine-Tuning Techniques: LoRA, QLoRA, Full Fine-Tuning
- Performance Metrics: BLEU, ROUGE, Perplexity, FID
- Scalability & Bias Considerations
- Hands-on Lab: Domain-Specific Fine-Tuning & Evaluation
MLOps, AIOps & Production Deployment
- Cloud Platforms & AIOps Pipelines: Jenkins, GitHub Actions
- Containerization & Serving: Docker, Kubernetes, FastAPI/Flask
- Observability & Monitoring: Logging, Metrics, Drift Detection
- Hands-on Lab: Containerizing & Deploying an AI Application
Responsible AI & Career Preparation
- Responsible AI Principles: Bias, Fairness, Transparency, Compliance (GDPR, HIPAA)
- Career Prep: Resume Building, Interview Readiness, Portfolio Development
- Hands-on Lab: Responsible AI Evaluation & Final Project Demo
Capstone Workshop
- End-to-End Solution Development with Domain-Specific Datasets
- Project Scoping, Data Preparation, Model Fine-Tuning & Benchmarking
Python & API Development Fundamentals
- Python Basics, Data Structures, Environment Setup
- FastAPI Essentials: RESTful APIs, CRUD, Pydantic Models, Unit Testing
- Hands-on Labs: Python Scripting, FastAPI Development, Testing
Cloud Deployment (AWS, Azure, GCP)
- Deploying Python & FastAPI Applications on AWS, Azure, and GCP
- Containerization with Docker, CI/CD Integration
- Hands-on Labs: Multi-Cloud Deployment of ML-Powered APIs
11+ Comprehensive Modules
200+ Hours of Training
Why Choose Quality Thought
Your success is our priority. Here’s what makes us the best choice for your career growth
17+
Years Experience
10,000+
Students Trained
500+
Hiring Partners
95%
Placement Rate
17+ Years of Excellence
Established training institute with proven track record of producing industry-ready professionals
Expert Faculty
Learn from trainers with 10+ years of real-world industry experience in leading tech companies
100% Placement Assistance
Dedicated placement cell with tie-ups with 500+ companies. We support you until you get hired
Comprehensive Curriculum
Updated syllabus covering latest technologies and industry best practices with hands-on projects
Career Growth Focus
Not just training, but complete career transformation with soft skills and interview preparation
Pay After Placement
Flexible payment options including pay after placement for eligible candidates
Flexible Batches
Multiple batch timings to suit working professionals, students, and freshers
Live Project Experience
Work on real client projects during internship at Ramana Soft IT company
We provide innovative placement solutions with direct access to hiring companies, paid internship programs, and comprehensive training that transforms freshers into job-ready professionals. Our proven methodology has helped thousands launch successful tech careers.
Certification
Get industry-recognized certification that validates your skills and boosts your career prospects
Certificate of Completion
Gen AI Development Program
This certifies that
[Your Name]
has successfully completed the
Gen AI Development Program
Training Program
Quality Thought
Ameerpet, Hyderabad
Certificate ID
QT-2024-XXXX
- Certificate Includes
- Industry-recognized course completion certificate
- Certification from Quality Thought institute
- Additional internship certificate from Ramana Soft (for I&I program)
- Digital certificate with unique verification ID
- Shareable on LinkedIn and other professional platforms
- Valid proof of skill acquisition for employers
- Includes detailed syllabus covered
- Project completion certificates
Industry Recognition
Our certificates are recognized by leading companies and add credibility to your resume
Skill Validation
Proves your expertise in Generative AI in all mentioned technologies
Career Advancement
Increases your chances of getting hired and helps in salary negotiations
Digital & Physical
Get both digital certificate for online sharing and physical certificate for framing
Course Certificate
Upon successful completion of training program
Internship Certificate
For I&I program from Ramana Soft IT Company
Project Certificate
For major projects completed during training
Frequently Asked Questions
Find answers to common questions about our Gen AI training program
Can a fresher learn generative AI development?
Yes, provided the order is right: this course teaches Python backend fundamentals before any LLM work, because an AI feature that cannot be versioned, tested, or deployed is not a notebook rather than a product. The program also introduces generative AI development with Python through practical development concepts.
What qualification do I need to join?
Any graduate or final-year student with comfort in basic logic can join. A computer science degree helps but is not required. Learners can build foundational skills through the program before exploring opportunities such as LLM engineer jobs USA.
Can I learn LLM development without knowing machine learning?
Yes. Working with existing models is application and systems engineering, so tokenisation, embeddings and evaluation concepts are enough, and no statistics or model-training background is assumed. The curriculum also introduces practical LLMOps training concepts relevant to working with LLM-based systems.
Is fine-tuning too advanced for a fresher?
No, because the course frames it as a decision rather than a research task: when to fine-tune, how to build and split a dataset, and how to measure whether the fine-tuned model actually beats the baseline. This structured approach can also support learners considering a career change to LLM engineer as they build practical AI engineering skills.
Is it realistic for a fresher to get an AI engineering job?
It is realistic but competitive. Freshers who succeed almost always have a deployed system and a public repository, and many enter through Python and backend roles and move into AI work internally. The program can also support Python developer to LLM engineer upskilling by connecting software development foundations with modern LLM engineering concepts.
What will my capstone project be?
Publish the actual named project rather than a generic claim. A specific deliverable, such as a retrieval system with published evaluation results deployed behind an API, is what makes the project useful when demonstrating your skills. Learners seeking generative AI training in Hyderabad can also explore the available training format and batch options.
How long before a fresher is job-ready?
Publish a realistic range only after checking it against actual learner outcomes. Avoid any implied guarantee. Learners researching is there a generative AI certification can separately review the certification details and course-completion requirements provided with the program.
Are freshers and working professionals taught in the same batch?
Confirm whether separate fresher and fast-track batches run, since a course spanning Python basics to LLMOps rarely serves both groups well in one cohort. For organizations that need structured team learning, LLMOps corporate training can provide a more focused approach based on the team’s requirements.
Is placement assistance available to freshers?
Yes, resume support, mock interviews and placement assistance are available to eligible learners including freshers, on completion of the course and capstone. Placement assistance is support, not a guarantee of a job offer. When comparing programs, learners can evaluate curriculum, projects and career support while researching the best LLM engineering course 2026.
What do freshers find hardest in this course?
Most freshers find evaluation hardest, because LLM systems fail non-deterministically and cannot be verified with a simple assertion, which is why the course teaches test sets and regression practice explicitly.
Ready to Start Your Career in Generative AI Development
Don’t wait. Get trained with hands-on labs and case studies, work on real-world projects from AI fundamentals to production deployment, and build your skills in Transformer architectures, LLMs, RAG, and Agentic AI. Your journey to becoming a Generative AI Developer starts here.
