AI Foundation

Master AI essentials from Python to machine learning and neural networks. Get hands-on with TensorFlow & PyTorch. Kickstart your AI career in Hyderabad with practical projects.

⏱ 3 Months🏫 Classroom📈 Beginner₹30,000₹25,000

Course Overview

So, you're looking to get into Artificial Intelligence? Smart move. This AI Foundation course isn't just theory; we're getting our hands dirty right from day one. You'll learn the core concepts, sure, but more importantly, you'll be building actual AI models using Python 3.9+, TensorFlow 2.x, and scikit-learn 1.3+. What good is knowing AI if you can't build anything? We start with Python programming essentials, then move quickly into data manipulation with Pandas and NumPy, before diving headfirst into machine learning algorithms like regression, classification, and clustering. By week 6, you'll be tackling neural networks and understanding deep learning principles. We'll even touch on basic natural language processing. Our expert trainers will guide you through 8 real-world projects. Want to work at places like Amazon Hyderabad or Microsoft IDC in Gachibowli? This foundation is crucial. Freshers in Hyderabad with these skills can expect starting salaries from ₹4.5 LPA to ₹7.5 LPA. We've seen hundreds of our students land their first AI roles. Plus, we offer flexible weekday and weekend batches at both our Dilsukhnagar and Ameerpet centers. Ready to build your future in AI?

What You Will Learn

✓ Build 8+ hands-on AI projects
✓ Master Python programming for AI
✓ Learn core Machine Learning algorithms
✓ Understand Neural Networks & Deep Learning basics
✓ Work with TensorFlow, Keras, and scikit-learn
✓ Get career guidance for Hyderabad AI roles
✓ Flexible weekend and weekday batch options
✓ Practical, trainer-led learning experience

Tools & Technologies

Python 3.9+NumPyPandasMatplotlibSeabornscikit-learn 1.3+TensorFlow 2.xKeras 2.xJupyter NotebookGoogle Colab

Syllabus

1Module 1: Python for AI & Data Science — Python fundamentals (data types, control flow), Functions, modules, and basic OOP, NumPy for numerical computing, Pandas for data manipulation & analysis, Matplotlib & Seaborn for data visualization+

2Module 2: Machine Learning Fundamentals — Introduction to ML: supervised vs. unsupervised learning, Data preprocessing (cleaning, scaling, encoding), Linear Regression & Logistic Regression, Decision Trees and Random Forests, K-Nearest Neighbors & Support Vector Machines+

3Module 3: Advanced Machine Learning & Evaluation — Clustering algorithms: K-Means, DBSCAN, Model evaluation metrics: accuracy, precision, recall, F1-score, Cross-validation and hyperparameter tuning (Grid Search), Feature engineering techniques, Introduction to NLP basics+

4Module 4: Deep Learning Foundations — Neural Network architecture: perceptrons, activation functions, Backpropagation algorithm explanation, Building ANNs with Keras and TensorFlow 2.x, Convolutional Neural Network (CNN) basics, Recurrent Neural Network (RNN) overview+

5Module 5: Practical AI Projects & Career Path — Building a sentiment analysis model project, Image classification project with CNNs, Recommender system basics implementation, Basic model deployment considerations, Preparing for entry-level AI/ML roles, Resume and interview preparation for Hyderabad job market+

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