Online Generative AI Course in Pune
Classroom • Live Online • Hybrid
Looking for a flexible way to learn AI? The Online Generative AI Course from 3RI Technologies in Pune lets you attend live classes, practice real projects, and understand how tools like GPT and modern LLMs are used in real applications.
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| EMI Plan | Registration | Percent |
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On Registration |
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2nd installment – 2nd month |
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Key Features
Course Duration: 4 months
Project Based Learning
Certification & Job Assistance
Real-Time Projects : 4
EMI Option Available
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Overview - Online Generative AI Course in Pune
An Online Generative AI Course in Pune allows students and working professionals to learn advanced AI technologies through live job-oriented training without needing to relocate or attend classroom sessions physically. With the rapid adoption of Generative AI across industries, many learners prefer flexible learning options that allow them to upgrade their skills while continuing their education or professional work.
Online training programs provide structured learning through interactive sessions, guided practical exercises, and project-based assignments, enabling students to develop real-world AI skills from anywhere. Through remote learning environments, students can participate in discussions, practice AI development tasks, and collaborate with mentors and peers.
This learning format makes it possible for learners across different cities and countries to access structured Generative AI training in Pune, industry-relevant curriculum, and mentorship from experienced trainers.
Online Generative AI training is suitable for learners who want to develop AI skills but prefer flexible learning environments.
The program is often chosen by:
- Students from computer science, IT, or engineering backgrounds
- Software developers interested in transitioning to AI development roles
- Data analysts or data scientists expanding their expertise into AI technologies
- Working professionals exploring automation and AI-powered tools
- Technology enthusiasts interested in building AI applications
For these learners, structured online training provides an opportunity to learn advanced AI technologies without disrupting their current academic or professional schedules.
The Online Generative AI Course at 3RI Technologies is conducted through live instructor-led sessions, allowing students to learn directly from experienced trainers while interacting in real time. These sessions include concept explanations, practical demonstrations, and guided exercises so learners can understand how Generative AI tools and models are applied in real-world scenarios.
To support flexible learning, all live classes are recorded and uploaded to the LMS platform, enabling students to revisit sessions whenever needed. This is particularly useful for working professionals or learners who want to revise complex topics such as prompt engineering, LLM workflows, or AI model integrations.
Dedicated doubt-clearing sessions and mentor support are also part of the online training process. Students can ask questions during live sessions, participate in scheduled Q&A discussions, or connect with trainers for guidance while working on projects and assignments. This ensures that even in an online format, learners receive structured support, continuous feedback, and practical learning guidance throughout the course.
Students often evaluate online and classroom training formats before enrolling in a Generative AI course. Each format has its own advantages depending on the learner’s schedule, learning style, and access to training centers. The table below highlights the practical differences to help students choose the most suitable learning mode.
Training Mode | Advantages | Limitations | Best Suited For |
Online Generative AI Training | Flexible learning from any location, ideal for working professionals; live instructor-led sessions with recorded backups; access to digital labs, assignments, and LMS resources; easier schedule management. | Requires strong self-discipline; limited in-person networking with peers; learning environment depends on internet connectivity and personal setup. | Working professionals, students outside Pune, learners who prefer remote or flexible schedules. |
Offline Classroom Training | Face-to-face interaction with trainers; immediate doubt resolution; structured classroom environment; stronger peer networking and collaboration on projects. | Fixed batch timings; travel time to the training center; less flexibility for professionals with irregular work schedules. | Fresh graduates, students who prefer classroom learning, learners who benefit from structured in-person guidance. |
Hybrid Learning (Online + Offline) | Combines flexibility of online sessions with classroom workshops; allows students to attend live classes remotely while joining important practical sessions in person; balanced learning approach. | Requires coordination between schedules; not all sessions may be available in both formats simultaneously. | Students looking for flexibility but also wanting occasional in-person interaction and project discussions. |
From a learning outcome perspective, the effectiveness of a Generative AI course depends more on the curriculum, practical projects, and trainer expertise than the training format itself. Students should evaluate factors such as hands-on practice, mentorship support, project exposure, and career guidance while choosing between online and offline training modes.
Online AI training programs are designed to provide flexibility and accessibility without compromising learning quality. Many learners today prefer remote training because it allows them to balance skill development with academic or professional commitments.
Some of the key benefits of choosing an online Generative AI course include:
- The ability to attend training sessions from any location
- Live interaction with trainers during concept explanations and demonstrations
- Flexible learning options suitable for working professionals
- Access to digital learning resources and recorded sessions for revision
- Opportunities to collaborate with learners from different technical backgrounds
For individuals who cannot attend classroom sessions due to location constraints or work schedules, online training provides an effective alternative to gain practical AI development skills.
Both online and classroom training formats provide structured learning environments, but they differ in terms of accessibility and flexibility.
Feature | Online Training | Classroom Training |
Learning Location | Attend from anywhere | Requires physical presence |
Schedule Flexibility | Suitable for working professionals | Fixed classroom schedules |
Trainer Interaction | Live sessions with real-time discussion | Direct in-person interaction |
Accessibility | Ideal for remote learners | Best for local students |
Students should choose the learning format that best suits their location, schedule, and preferred learning style.
To participate effectively in the Online Generative AI Course at 3RI Technologies, students need a basic technical setup that supports live training sessions, coding practice, and AI tool usage. Since the course includes hands-on work with programming environments, AI frameworks, and cloud-based tools, having the right system configuration ensures a smooth learning experience.
Requirement | Recommended Specification | Why It Is Needed |
Laptop / Desktop | Minimum 8 GB RAM, Intel i5 / Ryzen 5 processor or equivalent | Required for running Python environments, notebooks, and AI development tools during practical sessions. |
Operating System | Windows 10/11, macOS, or Linux | Compatible with Python, Jupyter Notebook, AI libraries, and development environments used during training. |
Internet Connection | Stable broadband connection (minimum 10 Mbps) | Ensures smooth participation in live sessions, screen sharing, and downloading datasets or project files. |
Web Browser | Latest version of Chrome, Edge, or Firefox | Needed to access the LMS platform, cloud tools, and AI development interfaces. |
Headset / Microphone | Optional but recommended | Helps in participating in live discussions, doubt-clearing sessions, and interactive workshops. |
Software Tools | Python, Jupyter Notebook, VS Code (installation guidance provided during the course) | Used for hands-on coding, AI model experimentation, and project development. |
Students are guided during the initial onboarding sessions on how to install the required tools and configure their development environment. This ensures that even learners with limited prior setup experience can prepare their systems properly before beginning practical Generative AI training.
Online Generative AI training programs typically follow a structured format similar to classroom-based courses, with additional digital tools that support remote collaboration and learning.
Training generally includes:
- Live virtual sessions conducted by experienced instructors
- Real-time demonstrations of AI models, tools, and frameworks
- Interactive doubt-solving discussions during classes
- Assignments designed to reinforce practical understanding
- Guided project development with mentor support
Students participate in these sessions using video conferencing platforms and collaborative coding environments, allowing them to follow demonstrations and practice AI implementation during the training itself.
This structured approach helps learners develop both theoretical understanding and practical experience with Generative AI technologies.
Students enrolled in the Online Generative AI Course receive access to a dedicated Learning Management System (LMS) designed to support structured and flexible learning. The platform acts as a central hub where learners can access class recordings, study materials, coding resources, assignments, and project documentation throughout the course duration.
The LMS also allows students to track their progress, revisit important Generative AI concepts, and practice using AI tools and frameworks covered during training. Features such as session replays, downloadable resources, and project submission portals help learners revise topics like prompt engineering, large language models, and AI application development at their own pace.
This system is particularly helpful for working professionals and remote learners, as it ensures continuous access to learning resources even after live sessions are completed.
One of the most important features of online Generative AI training is live instructor-led sessions, where students interact directly with trainers during the learning process.
In live sessions, trainers explain concepts such as:
- AI model fundamentals
- Prompt engineering techniques
- Generative AI application development
- AI integration with real-world software systems
Students can ask questions, participate in discussions, and observe how AI solutions are built step by step. This approach provides a more interactive learning experience compared to purely self-paced courses that rely only on recorded videos.
Real-time instructor guidance helps students understand how theoretical AI concepts are applied in practical development scenarios.
Modern Generative AI programs focus on building practical skills using widely used AI development tools and frameworks. During training, students are introduced to technologies commonly used for building AI-driven applications.
Typical topics and tools covered may include:
- Python programming for AI development
- Prompt engineering techniques for Large Language Models
- Generative AI APIs and frameworks
- Natural language processing concepts
- AI-powered automation workflows
- Deployment basics for AI-powered applications
Learning these technologies helps students understand how Generative AI solutions are built and integrated into real-world systems.
Practical project development is an essential part of Generative AI training. Through guided projects, students apply the concepts they learn during the course to build working AI applications.
Examples of projects in Generative AI programs may include:
- AI chatbot development
- Text generation or summarization tools
- AI-powered content automation systems
- Prompt-based productivity applications
Working on such projects allows students to gain practical experience in AI model usage, system integration, and problem solving. These projects can also become part of a professional portfolio when applying for AI-related roles.
Even in remote learning environments, students receive various forms of support throughout the training program. Continuous guidance ensures that learners are able to understand concepts and successfully complete practical assignments.
Support provided during online training may include:
- Trainer mentorship and technical guidance
- Doubt-solving sessions during or after classes
- Feedback on assignments and project work
- Guidance for building AI project portfolios
This structured support system helps ensure that online learners receive a learning experience comparable to classroom training.
Batch Schedule for Online Generative AI Training
Online courses are typically scheduled in multiple formats to accommodate different learner groups.
Common batch schedules include:
- Weekday batches for full-time learners
- Weekend batches designed for working professionals
- Evening sessions for individuals balancing work and learning
Flexible scheduling options allow learners to choose training sessions that fit their availability while maintaining consistent progress in the course.
Professionals who develop Generative AI skills can explore various roles across industries where AI technologies are being integrated into digital products and services.
Some of the common career paths include:
- Generative AI Engineer
- AI Application Developer
- Machine Learning Engineer
- Prompt Engineer
- AI Automation Specialist
As companies increasingly invest in AI-driven technologies, professionals with practical knowledge of Generative AI tools and frameworks are becoming valuable contributors to modern technology teams.
Yes. Students enrolled in the Online Generative AI Course at 3RI Technologies receive the same placement support services as classroom students. The career support process is designed to be accessible regardless of the training mode.
Placement assistance typically includes resume building sessions, LinkedIn profile optimization, mock technical interviews, HR interview preparation, and guidance on building a strong AI project portfolio. These sessions are conducted through live workshops, one-to-one mentoring calls, and virtual interview preparation sessions, ensuring online learners receive structured career guidance.
Students also receive support in project presentation, GitHub portfolio development, and interview readiness, which are key factors recruiters evaluate for AI-related roles. Since hiring processes for most technology roles already happen online through coding tests, virtual interviews, and technical assessments, online learners can participate in the same placement preparation activities as offline students.
The key factor that influences placement outcomes is the student’s project work, technical understanding, and interview readiness, not whether the course was completed online or in a classroom format.
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Prerequisite
Who can apply for this program?
- Graduates who want to become Generative AI engineer.
- BE / BTech / MCA passed aspirants to make their career in Generative AI.
- IT-Professionals who want to get career in Generative AI.
- Professionals from non-IT bkg, and want to establish in IT.
- Candidate who would like to restart their career after a gap.
- Infrastructure Management candidates for next level of their career.
Syllabus- Generative AI Course in Pune
The detailed syllabus is designed for freshers as well as working professionals
Decade Years Legacy of Excellence | Multiple Cities | Manifold Campuses | Global Career Offers
- Explore Artificial Intelligence (AI) and its core pillars: Machine Learning (ML), Natural Language Processing (NLP), Deep Learning (DL), and Reinforcement Learning (RL).
- Trace the history and evolution of AI.
- Discover transformative AI applications in industries like finance, healthcare, and retail.
- Understand the future potential of AI and its role in reshaping technology.
1. Introduction to Python
- Python Installation and setting up your Environment
- Get familiar with various Integrated Development Environments (IDEs) such as IDLE, PyCharm
- Start Python programming by learning to code in an interactive shell.
- Start programming on an interactive shell.
- Python Identifiers, Keywords
- Access Command line arguments within programs.
2. Conditional Statement, Loops and File Handling
- Python Data Types and Variable Condition and Loops in Python Python Modules & Packages
- Python Files and Directories manipulations
- Use various files and directory functions for OS operations
3. Python Core Objects and Functions Built in modules (Library Functions) Numeric and Math’s Module
- String/List/Dictionaries/Tuple
- Complex Data structures in Python Python built in function
- Python user defined functions
- The anonymous Functions – Lambda Functions
- Decorators
- Iterators and Iterable Generators
- Yield keyword
- Iterators Generators Difference
4. Modules & Packages
- Modules
- How to import a module…?
- Packages
- How to create packages
5. Data Manipulation with Pandas
- Data Frames Series
- Creating Pandas DataFrame Selection in DFs
- Data Describe Data info
- Retrieving in DFs
- Reshaping the DFs – Pivot Combining DFs
- Merge
- Concatenation
6. Introduction to NumPy
- Array Operations Arrays Functions
- Array Mathematics
- Mean
- Standard Deviation Max
- Min
- Array Manipulation
- Reshaping
- Resizing
- Random function
- Transpose
7. Visualization with Matplotlib
- Matplotlib Installation
- Matplotlib Basic Plots & it’ s Containers
- Matplotlib components and properties
- Scatter plots Histograms
- Bar Graphs Pie Charts Box Plots
1. Introduction to NLP, Text Preprocessing Methods
- Normalization
- Tokenization
- Stopword Removal
- Stemming & Lemmatization
2. Linguistic and Semantic Analysis
- Part-of-Speech (POS) Tagging
- Named Entity Recognition (NER)
- Sentiment Analysis
3. Text Vectorization Techniques
- Bag of Words (BoW)
- TF-IDF
4. Hands-on NLP Implementation
- Industry-standard library usage:
- spaCy for pipeline construction
- Hugging Face Datasets for model training/evaluation
1.Transformer Architecture Deep Dive
- Self-attention mechanisms
- Encoder-decoder structure
- Foundation models: BERT (bidirectional), GPT (autoregressive), and LLM variants
2. LLM Training Lifecycle
- Pretraining objectives
- Tokenization strategies: Byte-Pair Encoding (BPE), WordPiece and Embedding
- Fine-tuning overview
3. Prompt Engineering Mastery
- Zero-shot, few-shot, and chain-of- thought prompting
- Role-based prompting and persona injection
- Prompt optimization: iterative refinement, constraint specification, and output formatting
4. Hands-on Model Deployment
- Hugging Face Transformers
- Loading pretrained models and tokenizers
- Text generation with controllable parameters (temperature, top- k/p)
- OpenAI API integration:
- Request construction, response parsing, and cost management
- Safety filters and output validation
5. Application Development
- Build task-specific agents: summarizers, classifiers, and content generators
- Evaluate outputs for coherence, factual accuracy, and bias mitigation
1.RAG Architecture Fundamentals
- Workflow: retrieval → context injection → generation
- Advantages over pure LLM inference for domain-specific tasks
2. Embedding & Similarity Search
- Dense text embeddings (e.g., Sentence-BERT, E5)
- Vector similarity metrics: cosine, Euclidean, dot product
- Approximate nearest neighbor search algorithms
3. Document Processing Pipeline
- Data ingestion from diverse sources (PDFs, CSVs, web content)
- Chunking strategies: fixed-size, semantic, and overlap handling
- Metadata enrichment for filtered retrieval
4. Vector Database Implementation
- FAISS for efficient in-memory indexing
- ChromaDB for persistent, metadata- aware storage
- Index optimization and hybrid search (keyword + semantic)
5. Knowledge Bot Development
- Query parsing and intent recognition Context injection techniques:
- Response generation with citation and source attribution
6. RAG System Enhancement
- Query augmentation and expansion
- Re-ranking retrieved results for relevance
- Evaluation frameworks
1.Multimodal AI Foundations
- Multimodal datatypes: text, images, audio, video—and their fusion challenges
2. Key Multimodal Architectures
- CLIP: contrastive image-text pretraining
- BLIP: bootstrapped language-image pretraining for captioning
- Gemini and other unified multimodal foundation models
3. Multimodal Embeddings and Alignment
- Image-text embedding alignment
- Cross-modal similarity search and retrieval
4. Multimodal Application Development
- Image captioning and visual question answering (VQA)
- Multimodal chatbots with vision capabilities
5. Learn Real-World Use Cases
- Customer support automation with visual context
- Content creation: text-to-image generation, video description
1.Multi-Agent System Fundamentals
- Agent definition: autonomy, goals, and environmental interaction
- Collaborative vs. competitive agent architectures
2. Agent Design Principles
- Role specialization and responsibility assignment
- Task decomposition and planning
- Agent Communication protocols
3. Multi-Agent Workflow Orchestration Patterns
- Sequential workflows
- Parallel workflows
- Dynamic routing based on task complexity and agent capability
4. Agent Frameworks & Tooling
- LangGraph for stateful, cyclic agent workflows
- Microsoft AutoGen for conversational agent teams
- Task Automation
5. Advanced Orchestration – Multi-Agent Control Plane (MCP):
- Centralized coordination and scheduling
- Scalable deployment across compute resources
- Resource allocation and load balancing
6. End-to-End Automation
- Build autonomous systems for research, coding, and business process automation
- Monitor agent performance, handle
- failures, and enable self-correction
- Master SQL for data querying and management.
- Design REST APIs using FastAPI or Flask.
- Introduction to Git & Distributed Version Control
- Life Cycle
- Create clone & commit Operations
- Push & Update Operations
- Stash, Move, Rename & Delete Operations.
- Explore model monitoring, data drift, and LLMOps with tools like LangSmith,
MLflow, and Evidently. - Apply AI to domains like finance (fraud detection), healthcare (patient
chatbots), insurance (claim processing), HR (resume parsing), government
(policy summarization), airlines (customer service), and manufacturing (defect
detection).
- Showcase a full-stack Generative AI Capstone Project tailored to a real-world problem.
- Receive personalized feedback from mentors.
- Explore career paths like Prompt Engineer, GenAI App Developer, or AI Consultant.
- Join an exclusive GenAI alumni community for ongoing support.
- Tools & Frameworks: Python, SQL, Pandas, NumPy, Hugging Face, spaCy, LangChain, OpenAI, FastAPI, Streamlit, LangGraph, AutoGen, MLflow, Azure, Docker, and more.
- Mini Projects: Build a Resume Analyzer, PDF Q&A Bot, and Customer Support Assistant.
- Real-World Case Studies: Apply AI to finance, healthcare, insurance, HR, airlines, manufacturing, and government.
- What You’ll Receive: Weekly assignments, private GitHub access, mini project walkthroughs, a course completion certificate, career guidance, and exclusive alumni community access.
Course Highlights
Live sessions across 6 months
Industry Projects and Case Studies
24*7 Support
Project Work & Case Studies
Validate your skills and knowledge
Validate your skills and knowledge by working on industry-based projects that includes significant real-time use cases.
Gain hands-on expertize
Gain hands-on expertize in Top IT skills and become industry-ready after completing our project works and assessments.
Latest Industry Standards
Our projects are perfectly aligned with the modules given in the curriculum and they are picked up based on latest industry standards.
Get Noticed by top industries
Add some meaningful project works in your resume, get noticed by top industries and start earning huge salary lumps right away.
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Frequently Asked Questions – Online Generative AI Courses
Most frequent questions and answers
The Online Generative AI course at 3RI Technologies, Pune is designed for students, developers, IT professionals, and anyone interested in learning modern AI technologies. People who want to understand LLMs, prompt engineering, and AI-based applications can join the training.
The Online Generative AI training at 3RI Technologies focuses on concepts such as Large Language Models, prompt engineering techniques, AI tools, and real-world AI workflows. Learners also gain exposure to how Generative AI is used in chatbots, automation, and content generation systems.
Basic programming knowledge can be helpful, but it is not always mandatory. The Online Generative AI course in Pune at 3RI Technologies introduces important AI concepts step by step, helping learners gradually understand how LLMs and AI tools work in practical applications.
Yes, learners who successfully complete the Online Generative AI training at 3RI Technologies receive a Generative AI certification. This certification can be included in professional profiles to demonstrate knowledge of AI technologies, LLM concepts, and prompt engineering.
The Online Generative AI course at 3RI Technologies generally includes live instructor-led sessions where learners can interact with trainers, ask questions, and participate in discussions. Recorded sessions may also be available to help students review important concepts later.
Yes, the Online Generative AI training program at 3RI Technologies offers flexible batch timings, including evening or weekend options. This makes it easier for working professionals to upgrade their AI skills while continuing their regular job.
Yes, practical exercises are an important part of the Online Generative AI course at 3RI Technologies. Learners work on assignments and projects that help them understand how LLMs, prompt engineering, and AI applications are used in real scenarios.
The duration of the Online Generative AI course in Pune at 3RI Technologies depends on the training schedule and learning modules included. The program is structured to provide enough time for understanding concepts as well as practicing hands-on AI exercises and projects.
After completing the Online Generative AI training, learners may explore opportunities related to AI development, machine learning, and Generative AI applications. Understanding LLMs and prompt engineering can support roles connected with AI-powered products and automation systems.
To join the Online Generative AI course at 3RI Technologies in Pune, interested learners can contact the institute to check batch availability and course details. The team usually provides guidance about the training structure, schedule, and enrollment process.
Yes, the training integrates business-oriented case studies. Students gain a better understanding of how generative AI is used in actual business settings due to these exercises. Practical problem-solving is the main focus.
Yes, 3RI Technologies offers classroom training in Pune. Hybrid learning options are also available for flexible participation. The format that works best for them can be selected by the students.
Periodically, the curriculum is examined and updated to take consideration new developments in AI technology. Industry trends and employer requirements are considered while refining modules.
Yes, working professionals are included in the program’s design. Learning and work obligations can be balanced with the use of set times and flexible batch scheduling.
Yes, students learn the fundamentals of integrating and deploying AI models into applications. This ensures understanding beyond model building and into practical implementation.
The program emphasizes practical exposure, structured mentorship, and career-focused preparation. The goal is skill development aligned with real industry expectations.
Yes, students complete multiple projects and assignments.These can be used in interviews or portfolios. Portfolio development is encouraged throughout the training.
Generative AI is increasingly adopted across industries for automation and intelligent systems. Learning these skills positions students for emerging AI-driven roles.
You can connect with the 3RI Technologies counseling team for batch details and enrollment guidance. They will provide complete information about schedules and next steps.
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Pune is considered a student’s Paradise
Queen of the Deccan or Oxford of the East, Pune is known by various names because of its wonders. And why not? Most of the top universities and professional courses are established here. It is counted as the second-largest IT hub in India. Having a population of about 5.05 million, Pune is a livable city witnessing a peaceful and beautiful aura. Being a charming fusion of contemporary and traditional, Pune experiences several tourist attractions yearly.
Some of the most visited attractions of Pune are:
- Sinhagad Fort
- Shaniwar Wada
- BAPS Swaminarayan Temple
- Aga Khan Palace
- Saras Bag
- Pashan Lake
- Khadakwasla Dam
Undoubtedly, Pune is considered a student’s paradise and continuously sees growth. Students from all over India show interest in enrolling in different courses offered by various organizations.
The great job opportunities, fantastic weather, and unsurpassed education make this place the best. Savitribai Phule Pune University, run by women only, is now positioned in 9th among the top 10 universities in India. This clearly shows the rich legacy of Pune and why students prefer to come here for their bright future.
Pune offers over 800 colleges that cover over 400-course programs in numerous disciplines. It’s not just the University of Pune; other universities and private institutions offer multiple courses. For every reason, Pune provides everything to prospective students so that they can see their bright future ahead.
3RI Technologies is a world-renowned institute offering Software Development courses to aspiring professionals. Our course helps you in mastering Cloud Computing, Web Technologies, AI, and machine learning technologies. You will get hands-on experience to get a clear idea.
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