Generative AI is redefining every industry — from software development and healthcare to finance and design. Skillfloor's Generative AI course in Bangalore is built to give you practical mastery of the tools and concepts that are actively transforming how the world works. Whether you're a working professional looking to future-proof your career or a fresher eager to enter the AI space, this program delivers structured, mentor-led training that goes beyond theory.
Based in Bangalore — India's silicon valley — Skillfloor connects you with a thriving AI ecosystem, active hiring companies, and a peer network of like-minded learners. Our course blends foundational AI literacy with advanced prompt engineering, LLM application development, and creative AI workflows, so you leave with both the knowledge and the portfolio to stand out in today's competitive market.
₹60,000
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Skillfloor is a Government-Recognized Skill Development Institute under Startup India (DPIIT), offering career-focused certification programs in Analytics, Artificial Intelligence (AI), Data Science, Digital Marketing, SEO, and related domains. As one of India's largest training institutes, our courses emphasize hands-on projects, expert mentorship, and skills aligned with real hiring needs. With flexible learning options - online, offline, and hybrid, plus 100% scholarships for selective students, we make quality, job-ready education accessible.
Explore the program that aligns with your goals and take the next step with Skillfloor.
Bangalore-based, industry-connected: Direct access to Bangalore's tech ecosystem with hiring partners across MNCs, startups & AI product companies.
Learn from practitioners, not just instructors: Our trainers are working AI professionals who bring live use cases, real tools, and current industry knowledge to every session.
Flexible learning modes: Choose weekend batches, weekday evening classes, or fully online — designed around Bangalore's working professional schedule.
Outcome-focused placement support:Resume building, mock interviews, LinkedIn optimisation, and direct referrals to our hiring network — all included.
Small batch sizes, big attention: Capped batches ensure every student gets personalised feedback, doubt resolution, and mentor time — not a crowded classroom.
Curriculum updated every quarter:GenAI moves fast. Our syllabus is reviewed quarterly so you always learn what employers are actively looking for right now.
Hands-on AI tools training: Work directly with the latest Generative AI tools and platforms used in real projects. Gain practical experience with AI workflows, automation tools, and content generation systems.
Real-world project exposure: Apply your learning through industry-style assignments and practical case studies. These projects help you understand how companies use Generative AI in marketing, automation, and product development.
Portfolio that attracts recruiters: By the end of the program, you will have a strong AI project portfolio showcasing practical skills. This helps recruiters quickly evaluate your capabilities during hiring.
Career guidance for AI roles: Get guidance on career paths in Generative AI, including roles, required skills, and market demand. Mentors help you plan the right steps to transition into AI-related jobs.
- Overview of AI and ML
- Types of Machine Learning
- Data Collection and Preprocessing
- Basic Statistics for AI
- Python Essentials for AI
- Regression Analysis
- Classification Algorithms
- Ensemble Methods
- Model Evaluation Techniques
- Feature Engineering and Selection
- Introduction to Clustering
- Dimensionality Reduction Techniques
- Association Rule Learning
- Anomaly Detection
- Self-Organizing Maps (SOM)
- Introduction to Neural Networks
- Deep Neural Networks (DNNs)
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Autoencoders and Generative Models
- Introduction to NLP and Text Processing
- Text Classification and Sentiment Analysis
- Advanced NLP Techniques
- Deep Learning in NLP
- Speech Recognition and Processing
- Introduction to Computer Vision
- Image Classification with CNNs
- Object Detection Techniques
- Image Segmentation
- Video Processing and Analysis
- Introduction to Reinforcement Learning
- Markov Decision Processes (MDP)
- Q-Learning and SARSA
- Deep Q Networks (DQN)
- Applications of Reinforcement Learning
- Ethical Implications of AI
- Fairness and Bias in AI
- Privacy and Security Concerns
- Explainability in AI
- Legal and Regulatory Aspects
- AI in Healthcare
- AI in Finance
- AI in Manufacturing
- AI in Retail
- AI in Autonomous Systems
- Defining and Planning a Capstone Project
- Data Preparation for Projects
- Model Building and Testing
- Model Deployment Techniques
- Project Presentation and Evaluation