What will i learn?
- Master advanced AI & ML concepts including Deep Learning, Supervised & Unsupervised Learning.
- Gain expertise in industry-standard frameworks like TensorFlow and Keras for real-world projects.
- Learn to build, train, and deploy AI models for real-time business applications.
- Work on advanced live projects to strengthen your portfolio and job readiness.
- Certification will be provided by Udeck Services upon successful course completion.
Curriculum for this course
70 Lessons
00:00:00 Hours
Module 1: Advanced AI & ML Concepts
4 Lessons
00:00:00 Hours
- Difference Between AI, ML, Deep Learning, and Data Science 00:00:00
- AI in Business: Applications & Impact 00:00:00
- Ethical AI and Bias in Machine Learning 00:00:00
- Industry Trends & Future Scope 00:00:00
Module 2: Mathematics for AI & ML
4 Lessons
00:00:00 Hours
- Linear Algebra Essentials for ML 00:00:00
- Probability & Statistics for Machine Learning 00:00:00
- Calculus for Optimizing Models 00:00:00
- Matrices, Vectors, and Transformations 00:00:00
Module 3: Advanced Python for AI & ML
4 Lessons
00:00:00 Hours
- Python Data Structures Advanced (Sets, Dictionaries, Comprehensions) 00:00:00
- OOPs Concepts in Python for AI 00:00:00
- Advanced Functions, Decorators, Lambda Functions 00:00:00
- Virtual Environments & Package Management (pip, conda) 00:00:00
Module 4: Data Handling with Pandas, NumPy, Scikit-Learn
4 Lessons
00:00:00 Hours
- Advanced Data Manipulation Techniques 00:00:00
- Time Series, Text, and Image Data Handling 00:00:00
- Data Preparation for ML Models 00:00:00
- Feature Engineering, Dimensionality Reduction (PCA, LDA) 00:00:00
Module 5: Supervised Machine Learning in Depth
5 Lessons
00:00:00 Hours
- Linear Regression (Advanced Applications) 00:00:00
- Logistic Regression 00:00:00
- Decision Trees & Random Forest 00:00:00
- Support Vector Machines (SVM) 00:00:00
- Model Evaluation: Confusion Matrix, ROC, AUC 00:00:00
Module 6: Unsupervised Machine Learning in Depth
4 Lessons
00:00:00 Hours
- Clustering: K-Means, Hierarchical, DBSCAN 00:00:00
- Principal Component Analysis (PCA) 00:00:00
- Anomaly Detection 00:00:00
- Association Rule Mining (Apriori, FP-Growth) 00:00:00
Module 7: Model Evaluation, Optimization & Tuning
4 Lessons
00:00:00 Hours
- Cross-Validation Techniques 00:00:00
- Grid Search & Random Search for Hyperparameter Tuning 00:00:00
- Overfitting, Underfitting, Bias-Variance Tradeoff 00:00:00
- Performance Metrics: F1 Score, Precision, Recall 00:00:00
Module 8: Deep Learning Fundamentals
4 Lessons
00:00:00 Hours
- Introduction to Neural Networks (ANN) 00:00:00
- Activation Functions: ReLU, Softmax, Sigmoid 00:00:00
- Cost Functions & Backpropagation 00:00:00
- Gradient Descent Optimization 00:00:00
Module 9: Deep Learning with TensorFlow
4 Lessons
00:00:00 Hours
- TensorFlow Core Concepts (Tensors, Variables, Operations) 00:00:00
- Building Neural Networks with TensorFlow 00:00:00
- TensorBoard for Visualization 00:00:00
- Practical Applications with TensorFlow 00:00:00
Module 10: Deep Learning with Keras
4 Lessons
00:00:00 Hours
- Keras API Structure 00:00:00
- Sequential & Functional API Models 00:00:00
- Model Compilation, Training, Evaluation 00:00:00
- Transfer Learning with Pre-trained Models 00:00:00
Module 11: Computer Vision with Deep Learning
4 Lessons
00:00:00 Hours
- Image Classification (CNNs: Convolutional Neural Networks) 00:00:00
- Object Detection, Image Segmentation 00:00:00
- OpenCV Basics for AI 00:00:00
- Practical Projects: Image Recognition, Medical Imaging 00:00:00
Module 12: Natural Language Processing (NLP)
5 Lessons
00:00:00 Hours
- Text Preprocessing (Tokenization, Lemmatization, Stopwords) 00:00:00
- Sentiment Analysis 00:00:00
- Word Embeddings: Word2Vec, GloVe 00:00:00
- Sequence Models: RNN, LSTM 00:00:00
- Transformers & BERT (Introduction) 00:00:00
Module 13: Reinforcement Learning (Introduction)
4 Lessons
00:00:00 Hours
- RL Basics: Agents, Environment, Rewards 00:00:00
- Q-Learning 00:00:00
- Markov Decision Processes 00:00:00
- Practical Examples: Game AI, Robotics 00:00:00
Module 14: AI in Business – Practical Implementations
4 Lessons
00:00:00 Hours
- AI for Marketing Analytics 00:00:00
- AI for Financial Forecasting 00:00:00
- AI in Healthcare & E-commerce 00:00:00
- Industry Use Cases & Case Studies 00:00:00
Module 15: Advanced Real-Time Projects
5 Lessons
00:00:00 Hours
- Project 1: Predictive Modeling for Customer Churn (Classification) 00:00:00
- Project 2: Image Classification with CNN for Medical Diagnosis 00:00:00
- Project 3: Text Analytics for Sentiment Detection (NLP) 00:00:00
- Project 4: Stock Price Forecasting with LSTM (Time Series) 00:00:00
- Project 5: AI Chatbot for Customer Support 00:00:00
Module 16: Cloud Integration for AI & ML
3 Lessons
00:00:00 Hours
- Introduction to Cloud AI (AWS, Azure, Google Cloud) 00:00:00
- Deploying AI Models on Cloud Platforms 00:00:00
- APIs for AI & ML Services 00:00:00
Module 17: Career Preparation & Portfolio Development
4 Lessons
00:00:00 Hours
- Building a Professional Portfolio (LinkedIn, GitHub, Kaggle) 00:00:00
- Resume Preparation for AI & ML Roles 00:00:00
- Interview Preparation: Technical & HR 00:00:00
- Mock Interviews with Real-Time Questions 00:00:00
Requirements
- A Laptop or Desktop
- Basic Computer Knowledge
- Willingness to Learn and Practice
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Description
Udeck Services offers an in-depth Advanced AI & ML Training Course designed for graduates and professionals with prior experience in Python and data analysis. This course focuses on building advanced-level skills in machine learning, deep learning, and AI technologies used across industries today.
Students will explore advanced concepts like Supervised Learning, Unsupervised Learning, and Neural Networks while gaining practical, hands-on experience through live projects using TensorFlow and Keras. Emphasis is given to real-world applications of AI & ML, preparing learners for high-paying roles such as AI Engineer, Machine Learning Engineer, and Data Scientist.
By the end of the training, students will have mastered key tools, completed real-world AI projects, and will be job-ready for advanced roles in the IT and analytics sectors.
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Thu, 17-Jul-2025rahul kumar
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