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AI Course in Bangalore
At Apponix Academy, we offer hands-on training in our AI course in Bangalore. Master the most in-demand skills in Artificial Intelligence, Machine Learning, and Deep Learning under expert guidance. Our objective is to equip you with the skills and confidence needed to excel in the fast-growing AI industry.
In this AI certification course in Bangalore, we guide you with the standard tools used in the industry. We combine structured lessons with real time projects, use cases and technicals providing deeper insights and exposure. By the end of the course, you will have the technical expertise and the practical insights required to implement AI solutions effectively in professional environments.
Build a strong foundation in Artificial Intelligence and grow in your career with job-oriented training designed for the future of technology
2000+ Ratings
3000+ Happy Learners
60+Hours Live Training
3Industry Projects
LifetimeAccess to Course Materials
100%Placement Support
1-YearRecorded Access
Video Testimonials By Students From AI Course
Key Skills From Ai Course in Bangalore
Natural Language Processing
Convolutional Neural Networks
Neural Network Architecture
Predictive Model Building
Data Preprocessing Techniques
Feature Engineering Techniques
Model Performance Evaluation
Text Classification Methods
Regression Analysis Methods
Random Forest Models
Key Features of Ai Course
Industry-recognised certification
100% enrolment fee refund (T&C Applied)
Lifetime access to learning content
60+ hours of hands-on training
Practical Python training
TensorFlow & Keras exposure
Real-world case studies
Live, project-based learning
Expert industry mentors
Placement & interview support
Tools & Libraries Covered in AI course
Our Ai training programme in Bangalore covers essential python libraries used for various applications. You will gain practical, project-based experience with each tool through guided lab sessions and real-world case studies.
Python Programming
Learn Python fundamentals, data handling, functions, and coding techniques for AI and machine learning applications.
NumPy
Perform numerical computing, array operations, and mathematical processing for AI workflows.
Pandas
Clean, transform, analyse, and prepare datasets for machine learning projects.
Matplotlib & Seaborn
Create data visualisations, charts, and statistical plots to understand patterns and insights.
Scikit-learn
Build, train, evaluate, and optimise machine learning models using popular algorithms.
TensorFlow
Develop and train deep learning models for real-world artificial intelligence applications.
Keras
Build and experiment with neural networks using a simple and flexible deep learning framework.
Jupyter Notebook & Google Colab
Develop, test, visualise, and run AI and machine learning projects in interactive environments.
Our Alumni Working in Artificial Intelligence
Artificial Intelligence Course Reviews
Debashis guru
Associate Software Engineer
All the basics will get cleared with practical session, where command line is also been taught to us with a very friendly environment. Doubt solving is also done with good examples.
Maqsood Ali
Associate Software Engineer
This is the institute for learning the courses properly. You will get the full knowledge about the courses. The way of teaching is best.Thank you apponix
Rajendra Kumar
Associate Software Engineer
Apponix technology is a well-maintained sector where you can do your internship. Advanced staff, teaching style is very good. Not only knowledge gain but you will also get best experience.
Rakshita Yadalli
Software Engineer
I went to Apponix for Artificial Intelligence training, it was really good and wonderful. Trainer was highly hands on and the entire session was hands on. I would strongly recommend freshers and also experienced candidates to take this course at Apponix. Thanks a lot to Apponix team.
Sakshi Mishra
Software Engineer
Excellent training facility. Trainer was having depth knowledge about his subject. Really very good institute for Artificial Intelligence Course with best lab facility and good infrastructure. They provide real time training and placement assistance which is very good.
Our Recent Placements
Our Training Gallery
AI Training Fees in Bangalore
Class room Training
- Interactive Classroom Training Sessions
- 60+ hours of Practical Learning
- Guaranteed 5 Interview Arrangements
- Excellent Classroom Infrastructure
- Assured Job Placement
- Delivered by Working Professionals
Online Training
- Interactive Classroom Training Sessions
- 60+ hours of Practical Learning
- Guaranteed 5 Interview Arrangements
- Excellent Classroom Infrastructure
- Assured Job Placement
- Delivered by Working Professionals
Flexible Payment Options
- Zero-interest EMI available across major banks
- Instalment-based payment plans
- Group and student discounts on request
- Early enrolment discounts for upcoming batches
Call +91 80505 80888 or to receive the latest fee structure, discounts, and enrolment offers for the AI Course in Bangalore.
Upcoming Batches For AI Training in Bangalore
26-10-2026
- Weekday Batch (Mon–Fri)
- Start Date: 26 October 2026 | 8:00 AM – 9:30 AM IST
- Mode
- Classroom (Rajajinagar) / Online Live
- Duration
- 3 Months | 60+ Hours
Cannot find a batch that fits your schedule? Request a custom batch and our coordinators will arrange training at a time convenient for you.
Artificial Intelligence Course Syllabus
Artificial Intelligence
Module 1 - Decoding Artificial Intelligence
- Decoding Artificial Intelligence
- Meaning, Scope, and Stages Of Artificial Intelligence
- Three Stages of Artificial Intelligence
- Applications of Artificial Intelligence
- Image Recognition
- Applications of Artificial Intelligence - Examples
- Effects of Artificial Intelligence on Society
- Supervises Learning for Telemedicine
- Solves Complex Social Problems
- Benefits Multiple Industries
- Key Takeaways
Module 2 - Python for AI
- Python Basics and Data Types
- Working with Lists, Tuples, and Dictionaries
- Control Flow: Loops and Conditional Statements
- Functions and Reusable Code Blocks
- Introduction to Jupyter Notebook
- Key Python Libraries: NumPy, Pandas, Matplotlib, Scikit-learn
- Key Takeaways
Module 3 - Fundamentals of Machine Learning and Deep Learning
- Fundamentals Of Machine Learning and Deep Learning
- Meaning of Machine Learning
- Relationship between Machine Learning and Statistical Analysis
- Process of Machine Learning
- Types of Machine Learning
- Meaning of Unsupervised Learning
- Meaning of Semi-supervised Learning
- Algorithms of Machine Learning
- Regression
- Naive Bayes
- Naive Bayes Classification
- Machine Learning Algorithms
- Deep Learning
- Artificial Neural Network Definition
- Definition of Perceptron
- Online and Batch Learning
- Key Takeaways
Module 4 - Statistics and Probability for AI
- Central Tendency: Mean, Median, Mode
- Understanding Data Distribution and Skewness
- Probability Basics and Applications in AI
- Standard Deviation and Variance
- Bias-Variance Tradeoff: Underfitting and Overfitting
- Outlier Detection and Treatment
- Correlation and Its Role in Feature Selection
- Key Takeaways
Module 5 - Machine Learning Workflow
- Learning Objective
- Machine Learning Workflow
- Get more data
- Ask a Sharp Question
- Add Data to the Table
- Check for Quality
- Transform Features
- Answer the Questions
- Use the Answer
- Key Takeaways
Module 6 - Core Machine Learning Algorithms
- Linear and Logistic Regression
- Support Vector Machines (SVM) and Kernels
- K-Nearest Neighbours (KNN)
- Naive Bayes Classification
- Decision Trees and Random Forest
- K-Means and Hierarchical Clustering
- Choosing the Right Algorithm for a Problem
- Key Takeaways
Module 7 - Performance Metrics
- Performance Metrics
- Need For Performance Metrics
- Key Methods Of Performance Metrics
- Confusion Matrix Example
- Terms Of Confusion Matrix
- Minimize False Cases
- Minimize False Positive Example
- Accuracy
- Precision
- Recall Or Sensitivity
- Specificity
- F1 Score
- Key Takeaways
Module 8 - Deep Learning Architectures
- Artificial Neural Networks (ANN): Structure and Working
- Convolutional Neural Networks (CNN) for Image Recognition
- Recurrent Neural Networks (RNN) for Sequential Data
- Introduction to TensorFlow and Keras
- Building and Training Your First Neural Network
- Key Takeaways
Module 9 - Natural Language Processing (NLP)
- Text Pre-processing and Noise Removal
- Tokenisation, Stemming, and Lemmatisation
- Feature Engineering: TF-IDF and Word Embeddings
- Named Entity Recognition and Part-of-Speech Tagging
- Text Classification and Sentiment Analysis
- Key Takeaways
Call Us On
+91 8050580888
AI Course Projects
Project 1
AI-Powered Medical Report Summarization & Diagnosis Assistant
Build an AI assistant that extracts key information from medical reports, generates concise summaries, and provides preliminary diagnostic insights using NLP and Generative AI.
Project 2
Personalized AI Shopping Assistant Using LLM, RAG & Vision AI
Develop an intelligent shopping assistant using LLMs, RAG, and Vision AI to deliver personalized product recommendations, compare prices, answer product queries, and enable visual search.
Project 3
Generative AI-Based Video Editing & Captioning
Create an AI-powered video editing solution using GenAI and Stable Diffusion to automate editing workflows, generate captions, and enhance visual content with minimal manual effort.
Our Top Instructors
Mr. Gauri Shankar
- He is a working professional and has over a decade’s worth of experience in Block chain technology
- He is currently associated with an MNC and is working as a senior Platform Engineer
- Over the years, he has been our preferred block chain technology trainer here at Apponix
- he has trained more than 500 students in Block Chain Technology.
- He is a master when it comes to block Chain and teaching his students about configuration management tools
Overview Of AI Course In Bangalore
Our AI Course In Bangalore is designed to give you a complete understanding of how intelligent systems work, the skills required to build them, and how they are applied across industries.
The course begins by decoding Artificial Intelligence, covering its meaning, scope, and real-world applications such as image recognition and telemedicine. You will then build practical Python skills, including NumPy, Pandas, Scikit-learn, and Matplotlib.
Next, the fundamentals of Machine Learning and Deep Learning, supported by a Statistics and Probability module covering data distribution, correlation, and the bias-variance tradeoff. You will work through the machine learning workflow and core algorithms, including SVM, KNN, Decision Trees, Random Forest, and clustering, and learn how to choose the right approach for a given problem.
Performance evaluation using accuracy, precision, recall, and F1 score leads into Deep Learning Architectures, where you will build ANN, CNN, and RNN models using TensorFlow and Keras. The course concludes with Natural Language Processing, covering text pre-processing and classification techniques used in applications such as sentiment analysis and chatbots.
Whether you are starting out or upskilling, the course runs for 60+ hours of instructor-led training across classroom and online batches, with transparent and affordable fees.
Program Highlights
Our AI Course In Bangalore is built to give you both strong theoretical grounding and practical, job-ready skills. Here's what sets the programme apart:
- 60+ hours of instructor-led training across classroom and online batches
- Hands-on exposure to Python, TensorFlow, and Keras, the tools used by AI professionals in the industry
- Comprehensive curriculum covering machine learning, deep learning, and natural language processing
- Real-world projects and case studies to build practical, applicable skills
- Expert mentors with industry experience guiding you through every module
- Industry-recognised certification on successful course completion
- Dedicated placement assistance, including interview preparation and career support
- Lifetime access to self-paced learning content curated by industry experts
- 100% refund on your enrolment fee, minus administrative charges, if you're unsatisfied
Why Learn AI in Bangalore?
Bangalore is home to a large concentration of technology companies, product firms, and AI-focused startups, making it one of the strongest job markets in India for AI talent. Learning AI in Bangalore gives you direct access to:
- A dense network of IT and product companies actively hiring for AI roles
- Frequent AI and machine learning meetups, conferences, and hackathons
- A strong peer community of learners and working professionals
- Better visibility for internships and placement opportunities with local employers
You do not need a specialised degree to begin learning AI. If you have the interest and are willing to put in consistent practice, our structured curriculum is designed to take you from the fundamentals to job-readiness.
Career Benefits of Our Artificial Intelligence Course in Bangalore
- High Demand – AI skills are in demand across technology, healthcare, finance, and e-commerce sectors.
- Lucrative Salaries – Earn competitive pay with opportunities to grow into senior roles like AI Architect or Machine Learning Manager.
- Real-World Impact – Use AI to solve real business and societal challenges.
- Recognized Certification – Showcase your mastery of the fundamentals of Artificial Intelligence with our industry-recognized credential.
Related job roles
- Business Intelligence Developer
- AI Engineer
- Machine Learning Engineer
- Robotic Scientist
- Research Scientist
Generative AI vs Artificial Intelligence: What's the Difference?
Artificial Intelligence (AI) is a broad field focused on building systems that can perform tasks that typically require human intelligence, such as learning, reasoning, prediction, perception, and decision-making. Generative AI is a specialised area of AI that focuses on creating new content such as text, images, code, audio, and video.
| Aspect | Artificial Intelligence (AI) | Generative AI |
|---|---|---|
| Primary Focus | Building systems that perform intelligent tasks | Creating new content using AI models |
| Core Technologies | Machine Learning, Deep Learning, NLP, Computer Vision, Robotics | LLMs, Transformers, Diffusion Models, RAG, Multimodal AI |
| Typical Applications | Predictive analytics, recommendation systems, fraud detection, automation, computer vision | AI chatbots, content generation, code generation, image generation, AI assistants |
| Common Models | Regression, Decision Trees, Neural Networks, CNNs, RNNs | GPT-style LLMs, diffusion models, multimodal models |
| Programming Skills | Python, ML frameworks, statistics and algorithms | Python, APIs, LLM frameworks, prompt engineering, RAG |
| Output | Predictions, classifications, decisions, recommendations | Text, images, code, audio, video and other generated content |
| Typical Roles | AI Engineer, Machine Learning Engineer, Data Scientist | Generative AI Engineer, AI Engineer, LLM Engineer |
| Learning Curve | Moderate to Advanced | Moderate to Advanced |
| Career Scope | Broad applications across industries | Rapidly expanding applications in AI-powered products and workflows |
Which one should you learn? If you want to understand how intelligent systems are built, Artificial Intelligence provides the broader foundation across Machine Learning, Deep Learning, NLP, Computer Vision, and other AI technologies. If your goal is to work with LLMs, AI assistants, RAG applications, prompt engineering, multimodal models, and AI content generation, Generative AI provides a more specialised learning path. For learners looking to build practical AI applications, an AI course in Bangalore can combine foundational AI concepts with hands-on Generative AI projects, helping you understand both the underlying technologies and their real-world applications.
