Skill Development
Artificial Intelligence
Master Artificial Intelligence and Machine Learning with hands-on training. Build real AI models and get job-ready.
4.8 rating
250+ enrolled
2 Months
Beginner to Advanced
Prerequisite Knowledge: NONE | Education Background: ANY
Start Your Artificial Intelligence Journey
Join 250+ students already enrolled. Get certified and job-ready.
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This program includes
Industry certificate
Live + recorded sessions
Job placement support
Lifetime access to material
Small batch — personal attention
15+ language support
Recognition
Certification
Official Certification
Earn your certificate and stand out in the job market
Artificial Intelligence
Industry recognised certificate
Add to LinkedIn & resume
QR code verification
What You’ll Achieve
Course Outcomes
Build and deploy real AI models using Python
Master Machine Learning algorithms end-to-end
Work with Neural Networks and Deep Learning
Implement Natural Language Processing solutions
Use TensorFlow, Keras, and PyTorch confidently
Analyse data with Pandas and Matplotlib
Build a job-ready AI portfolio with live projects
Get placed as AI/ML Engineer in top companies
Skill Coverage
Skill-Sets Covered in Data Science & AI Program
Data Analytics / Business Analytics
Data Visualisation
Machine Learning Algorithms
Statistics
Ensemble Techniques
Natural Language Processing
Forecasting Analytics
Generative AI
Tools & Technologies You Will Learn
Python
TensorFlow
PyTorch
Pandas
NumPy
Jupyter
MySQL
Anaconda
Matplotlib
Scikit-learn
Keras
SQL ServerTableau, Power BI, Seaborn & more
Prerequisite Knowledge
NONE REQUIRED
Education Background
ANY
Age Group
18+ Years
Mode
Classroom + Online
Curriculum
Course Syllabus
1Introduction to Data Science & AI
- What is Data Science and Artificial Intelligence?
- Real-world applications of AI across industries
- Setting up your Python development environment
- Introduction to Jupyter Notebook and Anaconda
2Python for Data Science
- Python basics — variables, loops, functions
- NumPy for numerical computing
- Pandas for data manipulation and analysis
- Data cleaning and preprocessing techniques
3Data Visualisation
- Matplotlib and Seaborn for charts and graphs
- Power BI and Tableau dashboards
- Storytelling with data
4Statistics & Probability
- Descriptive and inferential statistics
- Probability distributions
- Hypothesis testing
- Statsmodels in Python
5Machine Learning Algorithms
- Supervised Learning — Regression and Classification
- Unsupervised Learning — Clustering
- Ensemble methods — Random Forest, XGBoost
- Model evaluation and cross-validation
6Deep Learning & Neural Networks
- Artificial Neural Networks (ANN)
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- TensorFlow and Keras hands-on
7Natural Language Processing (NLP)
- Text preprocessing and feature extraction
- Sentiment analysis and text classification
- Transformers and BERT basics
8Generative AI & Forecasting
- Introduction to Generative AI and LLMs
- Time series analysis and forecasting
- Real-world AI project implementation
- Portfolio building and interview preparation
