Artificial Intelligence Courses Online
✅ Learn AI Online from experts working in top tech companies
✅ Learn AI from scratch or only a portion that matters to you
✅ Career mentorship, resume support, and mock interviews etc.,
✅ Real-world, hands-on projects to build your portfolio
✅ Industry-recognized certifications
Learn First, Pay Later Pay Only if You're 100% Satisfied
10 Reason to Learn Artificial Intelligence
AI professionals earn ₹18–₹25 LPA on average, with even higher salaries in top MNCs.
India alone is expected to create over 10 lakh AI jobs by 2026 — and demand keeps rising.
AI is transforming every industry — from healthcare to finance — making it a skill of the future.
Professionals are shifting from IT and analytics into AI for better roles, pay, and global exposure.
Top companies like Google, Amazon, and Microsoft are hiring AI experts across the globe.
For every 10 AI jobs, there’s just 1 skilled professional — making YOU extremely valuable.
Contribute to exciting innovations like self-driving cars, chatbots, robotics, and GenAI tools.
Whether you’re from IT, data, marketing, or even non-tech, AI welcomes all learners.
Set to grow from ₹66,000 Cr to ₹1.4 Lakh Cr by 2027 — opening up massive opportunities.
AI is not just a trend — it’s the future. Learning it now means staying relevant tomorrow.
PLACEMENT RECORD
We’re proud of our alumni who now work at top companies. Although we keep their names private, we’re happy to share details if you request.
Syllabus Basics
- Introduction to Data Science Deep Learning & Artificial Intelligence
- Introduction to Deep Learning & AI
- Deep Learning: A revolution in Artificial Intelligence
- Limitations of Machine Learning
- What is Deep Learning?
- Need for Data Scientists
- Foundation of Data Science
- What is Business Intelligence
- What is Data Analysis
- What is Data Mining
- What is Machine Learning?
- Analytics vs Data Science
- Value Chain
- Types of Analytics
- Lifecycle Probability
- Analytics Project Lifecycle
- Advantage of Deep Learning over Machine learning
- Reasons for Deep Learning
- Real-Life use cases of Deep Learning
- Review of Machine Learning
- Basis of Data Categorization
- Types of Data
- Data Collection Types
- Forms of Data & Sources
- Data Quality & Changes
- Data Quality Issues
- Data Quality Story
- What is Data Architecture
- Components of Data Architecture
- OLTP vs OLAP
- How is Data Stored?
- What is Big Data?
- 5 Vs of Big Data
- Big Data Architecture
- Big Data Technologies
- Big Data Challenge
- Big Data Requirements
- Big Data Distributed Computing & Complexity
- Hadoop
- Map Reduce Framework
- Hadoop Ecosystem
Syllabus Intermediate
- What Data Science is
- Why Data Scientists are in demand
- What is a Data Product
- The growing need for Data Science
- Large Scale Analysis Cost vs Storage
- Data Science Skills
- Data Science Use Cases
- Data Science Project Life Cycle & Stages
- Data Acquisition
- Where to source data
- Techniques
- Evaluating input data
- Data formats
- Data Quantity
- Data Quality
- Resolution Techniques
- Data Transformation
- File format Conversions
- Annonymization
- Python Overview
- About Interpreted Languages
- Advantages/Disadvantages of Python pydoc.
- Starting Python
- Interpreter PATH
- Using the Interpreter
- Running a Python Script
- Using Variables
- Keywords
- Built-in Functions
- StringsDifferent Literals
- Math Operators and Expressions
- Writing to the Screen
- String Formatting
- Command Line Parameters and Flow Control.
- Lists
- Tuples
- Indexing and Slicing
- Iterating through a Sequence
- Functions for all Sequences
- Operators and Keywords for Sequences
- The xrange() function
- List Comprehensions
- Generator Expressions
- Dictionaries and Sets
- Learning NumPy
- Introduction to Pandas
- Creating Data Frames
- GroupingSorting
- Plotting Data
- Creating Functions
- Slicing/Dicing Operations
- Functions
- Function Parameters
- Global Variables
- Variable Scope and Returning Values
- Sorting
- Alternate Keys
- Lambda Functions
- Sorting Collections of Collections
- Classes & OOPs
- What is Statistics
- Descriptive Statistics
- Central Tendency Measures
- The Story of Average
- Dispersion Measures
- Data Distributions
- Central Limit Theorem
- What is Sampling
- Why Sampling
- Sampling Methods
- Inferential Statistics
- What is Hypothesis testing
- Confidence Level
- Degrees of freedom
- What is pValue
- Chi-Square test
- What is ANOVA
- Correlation vs Regression
- Uses of Correlation & Regression
Syllabus Advanced
- ML Fundamentals
- ML Common Use Cases
- Supervised and Unsupervised Learning
- Clustering
- Similarity Metrics
- Distance Measure Types: Euclidean, Cosine Measures
- Predictive Models
- K-Means Clustering
- TF-IDF & Cosine Similarity
- Case Study
- Association Rules & Recommendation Systems
- What is Association Rules
- What is Recommendation Engine
- Case Studies
- Supervised Learning Techniques
- Decision Tree
- Random Forest
- Naive Bayes
- Case Studies
- Regression Models
- Linear Regression (Simple & Multiple)
- Logistic Regression
- Model Evaluation – AUC, ROC, Validation
- Support Vector Machines
- SVM Concepts
- Kernel Trick
- Case Study
- Time Series Analysis
- ARIMA, ETS Models
- Forecasting
- Decomposition
- Visualization
- Case Study
- Feature Selection Techniques
- Preprocessing
- Scaling
- Final Project
- Cross Validation
- GridSearchCV
- Comparison of ML Models
- Sentiment Analysis
- NLP Techniques
- Case Study
- Spark Core
- Spark Architecture
- RDDs
- MLlib
- PySpark Basics
- ANN Overview
- Activation Functions
- Backpropagation
- Gradient Descent
- MLP Digit Classifier
- Deep Networks
- Use Case Implementation
- CNN Architecture
- Pooling, ReLU, Softmax
- Image Classification
- RNN Concepts
- LSTM in Python
- Restricted Boltzmann Machine
- Autoencoder Concepts
- Applications
- Model Building
- Introduction to TensorFlow
- Tensors, Graphs, Training
- MNIST Example
- Visualizations with TensorBoard
- Transfer Learning
- Google Inception
- Keras vs TFLearn
More Courses
You might also be interested in these courses
Course 1
IT Support Agentic AI Project Course
Learn AI with Real Projects
Course 2
Learn ML with Real Projects
Learn ML with Real Projects
Course 3
Learn Python Programming
Learn Python Programming
Course 4
LEARN MACHINE LEARNING COURSES ONLINE
LEARN MACHINE LEARNING COURSES ONLINE
Course 5
Learn DATA SCIENCE COURSES ONLINE
Learn DATA SCIENCE COURSES ONLINE
FAQ
Yes! We offer the first few classes completely free. You can explore the course, experience our teaching style, and decide later if you’d like to upgrade to the advanced modules or project-based training.
Just click on “Start Free Classes Now” and register. You’ll instantly get access to the free content and updates about upcoming sessions. No credit card or payment required to begin.
The introductory classes are free. You only pay for advanced modules or project training. Fees are affordable and structured per module. [Download the brochure] or [Contact us] for the latest pricing.
No prior programming experience is required. Our course starts from the basics and gradually moves to advanced concepts.
AI offers high-paying careers in Machine Learning, Data Science, Robotics, NLP, Computer Vision, and Generative AI. Roles include AI Engineer, Data Scientist, ML Specialist, and more.
Yes. We focus on project-based learning. You’ll build real-time projects to understand practical implementation.
Absolutely! We provide doubt-clearing sessions and post-class support via chat, calls, and email.
Yes, a course completion certificate will be provided, which is helpful for your resume and job interviews.
You’ll use tools like Jupyter Notebook, Google Colab, TensorFlow, Keras, Python, Pandas, NumPy, and cloud-based platforms for deployment and model testing.
Just Python (Anaconda), Jupyter/Colab, and a basic code editor like VS Code. We’ll guide you through all installations step-by-step.
Yes! The curriculum is designed for career transitions. We’ve helped IT professionals, analysts, and even business managers switch to AI successfully.
We recommend 6–8 hours/week, including live sessions, practice, and project work. Flexible options are available for working professionals.
Yes, we specialize in helping businesses find and hire the right talent. Our HR and recruitment services are tailored to meet your company’s specific hiring needs. Contact us to learn how we can support your hiring process.
Please visit our page : WoCons – Custom AI & CAD Solutions | Bengaluru