At Netmax Technologies, you learn generative AI by building. Every concept is followed by a coding exercise in our lab or on Google Colab, and the course ends with a capstone project you can show to employers. We help with your resume, LinkedIn and interview preparation, and share openings with hiring partners across the Tricity. We cannot promise a job, because that depends on your skills and your interviews.
20 Modules Series
Earn a certification that demonstrates your expertise in Generative AI Course
Beginner Level
No previous experience with coding is required
1.5 months
1.5 hours/day class
Flexible Schedule
Online/ Offline both modes of classes available.
Are you looking for the Best Institute for the Generative AI Course in Chandigarh, then don’t worry you are at the right platform. NetMax is here to provide you with the full Generative AI Course with practical knowledge and We even provide our candidates with the lab facilities and 100% Placement Assistance .
Duration: 4 weeks (1 month)
• Objective: Equip learners with theoretical knowledge and practical skills
in generative AI, including foundational models, large language models
(LLMs), LangChain, and real-world applications.
• Prerequisites: Basic knowledge of Python, machine learning concepts, linear algebra, and probability.
• Tools: Python, TensorFlow/PyTorch, Jupyter Notebooks, Hugging Face, LangChain,
NumPy, Pandas, Google Colab.
• Assessment: Weekly assignments and a final capstone project.
• Topics:
– Overview of generative AI: Applications (e.g., image generation, text
generation, music synthesis) and types of models (VAEs, GANs, diffusion models, LLMs).
– Key concepts: Probability distributions, likelihood, latent spaces.
– VAEs: Encoder-decoder framework, KL-divergence, reparameterization trick, and applications (e.g., image denoising, data generation).
• Activities:
– Lecture: Introduction to generative AI, its impact, and VAE theory.
– Hands-on: Set up Python environment (TensorFlow/PyTorch, Google
Colab, LangChain) and implement a simple VAE for MNIST digit generation.
– Assignment: Explore a generative AI tool (e.g., DALL·E mini) and train
a VAE on a dataset like Fashion-MNIST, analyzing the latent space.
• Learning Outcomes:
– Understand the scope of generative AI and VAE theory.
– Set up a development environment and generate synthetic data using
VAEs.
Perplexity
BLEU,
ROUGE
METEOR
Learn from trainers who work on Python, machine learning and AI projects, not from slides.
Finish with a Netmax completion certificate and a capstone project you can add to your resume and GitHub.
Join in class at our Sector 34A campus or attend live online. Assignments and support are the same in both.
62 coding exercises and weekly assignments. You write code in every class.
LLMs, LangChain, Hugging Face, prompt engineering and diffusion models are part of the syllabus.
Call 8699644644 for the latest fee. Installment options are available. Try a free demo first.
Ask doubts live in class and get one-to-one help from your trainer when you are stuck.
Practice on Python, Google Colab, Hugging Face, LangChain, TensorFlow/PyTorch and Streamlit.
B.Tech, BCA, MCA, B.Sc and similar students who want a practical AI skill before placements.
Developers, analysts and testers who want to add GenAI skills to their current role.
Comfortable with computers? Start here and move into AI roles step by step.
Build AI tools and automations for your own work or your clients.
Call us on: +91 8699644644 and take your 2 days free Demo classes
Here is the course explained in plain words, so you can decide before you call or visit. If anything stays unclear,
sit in a free demo class and see how we teach.
It is a type of artificial intelligence that creates new content. That content can be text, images, code, audio or video. The model learns patterns from a large amount of existing data, then produces something new that follows those patterns.
ChatGPT and Gemini write text. Stable Diffusion and DALL·E make images. All of them are built on ideas you study in this course, such as transformers, GANs, VAEs and diffusion models.
The course takes about 6 weeks, at 1.5 hours a day. Most of that time goes into coding, not slides. You complete 62 coding exercises, get weekly assignments and finish with a capstone project.
You work in Python with Jupyter Notebook and Google Colab. The tools include TensorFlow, PyTorch, Hugging Face, LangChain, NumPy and Pandas. You also work with LLMs through APIs and build small apps with Streamlit.
In week one, you set up Python, Google Colab and LangChain. Then you build a simple variational autoencoder (VAE) that generates handwritten digits from the MNIST dataset. For the assignment, you try a tool like DALL·E mini and train a VAE on Fashion-MNIST to see how the latent space behaves.
It is a small result. But it shows how the whole course works. You learn an idea, then you build it the same week.
You start with the maths behind generative AI (probability, statistics, linear algebra and calculus) and the basics of machine learning and deep learning. Then you move to generative models such as VAEs, GANs and flow-based models, followed by diffusion models like Stable Diffusion. After that come transformers, LLMs and prompt engineering (zero-shot, few-shot and chain-of-thought). The last part covers efficient training with LoRA and quantization, and how to judge a model with metrics like perplexity, BLEU, ROUGE and FID.
Companies use it for chatbots and virtual assistants, translation, photo editing, video generation, music, medical imaging and document generation. Teams in marketing, software, customer support and design already use these tools in daily work. So employers look for people who can use them with care, not just type a prompt.
The course suits college students, fresh graduates, working developers or analysts, and people switching careers. You do not need to be an expert, and we cover Python basics at the start.
But be honest with yourself. There is real maths in this course, and a lot of coding. If you can practise a little every day, you can handle it.
If you only want to use AI tools better at work, our Prompt Engineering course may fit you more. If you want to build AI agents later, finish this course first and then look at our Agentic AI course.
Benefits of Netmax Certificate
Netmax Industry-oriented Certificate validates the practical skills you have gained during training
Add your Netmax Certificate to your resume and Linkedin profile to stay ahead of the competition
Share your Certification with employers to highlight your capabilities & Job ready Proficiency
| Role | What you do | Skills from this course |
|---|---|---|
| Junior AI Engineer | Help build and test AI features inside products. The work is mostly Python, model work and fixing what breaks. | Deep learning, TensorFlow/PyTorch, Hugging Face |
| Generative AI Developer | Build apps on top of LLMs, such as chatbots, document tools and small assistants. | LLM APIs, LangChain, Streamlit |
| Prompt Engineer | Write and test prompts so an AI tool gives reliable answers. Rarely a standalone fresher role, so treat it as an extra skill. | Zero-shot, few-shot and chain-of-thought prompting |
| Automation Developer | Connect AI tools with daily business work, like replying to enquiries, sorting documents or preparing reports. | Python, APIs, web scraping |
| Data Analyst with AI skills | Analyse data as usual, and use AI to clean it, find patterns and explain results faster. | Pandas, NumPy, Python |
A certificate alone rarely gets an interview. Your work does. By the end you will have your coding exercises and a capstone project. Put them on GitHub, explain them in your resume and be ready to talk about how you built them. Interviewers like candidates who can explain their own project.
How we support you
We help with your resume and LinkedIn profile, take mock interviews and share openings from hiring partners across the Tricity. We do not promise a job or a salary. That depends on your skills, your projects and how you do in interviews.
We at Netmax Technology provide Job Assistance and most of the students have secure their job in various companies. Also, We have tieups with many companies in Tricity.
The course is available for the duration of both 45 days and 6 months including 1.5 hours of classroom training and 1.5 hours of practical assignments.
For this course, there are no particular requirements. However, having a basic understanding of computers and the internet is helpful.
We provide classes both in-person and online. The format that best meets your needs can be selected.
The course covers a wide range of modules such as python, machine learning , deep learning , neural network and details of which can be found on our website.
Yes, you will receive a certification from our institute after completing the course successfully.
You will gain practical expertise with a range of website strategies and tools through the completion of case studies, real-world projects, and assignments.
Our professors are professionals in the field with years of experience. They bring practical knowledge and real-world insights to the classroom.
You will be able to communicate with teachers and other students in one-on-one mentorship sessions.
Yes, we provide career support by helping in resume building, interview preparation, and job placement assistance.
By going to our website and completing the online registration form, you can register. As an alternative, you can come to our institute to finish the registration procedure.
Completing an application, attending a brief interview, and paying the course price are all part of the admissions process.
Yes, we occasionally give out a variety of discounts. To learn more, please get in touch with our admissions office.
After completing a course in web designing, you can pursue job roles such as Machine learning Engineer, software Developer and Data scientist.
Yes, we offer job placement assistance through our network of industry partners.
