Machine Learning & Deep Learning Online Live Class by Experts
Our Training/Internship Process
Machine Learning & Deep Learning - Syllabus, Fees & Duration
Introduction to Machine Learning
- Introduction to Artificial Intelligence
- Machine Learning Fundamentals
- Types of Machine Learning
- Real-World Applications
Python for Machine Learning
- Python Basics
- NumPy
- Pandas
- Matplotlib & Seaborn
Data Preprocessing
- Data Cleaning
- Handling Missing Values
- Feature Scaling
- Encoding Categorical Data
Exploratory Data Analysis
- Data Visualization
- Correlation Analysis
- Feature Selection
- Outlier Detection
Supervised Learning
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Support Vector Machines (SVM)
- k-Nearest Neighbors (KNN)
Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- DBSCAN
- Principal Component Analysis (PCA)
Model Evaluation
- Train-Test Split
- Cross Validation
- Confusion Matrix
- Accuracy, Precision, Recall & F1 Score
Introduction to Deep Learning
- Artificial Neural Networks
- Perceptron
- Activation Functions
- Forward & Backpropagation
TensorFlow & Keras
- TensorFlow Basics
- Keras API
- Building Neural Networks
- Model Training & Evaluation
Deep Learning Architectures
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- LSTM & GRU
- Transfer Learning
Computer Vision
- Image Classification
- Object Detection Basics
- Image Augmentation
- OpenCV Introduction
Natural Language Processing
- Text Preprocessing
- Tokenization
- Word Embeddings
- Text Classification
Model Deployment
- Model Serialization
- Flask/FastAPI Integration
- REST API Development
- Deployment Basics
Real-World Projects
- House Price Prediction
- Customer Churn Prediction
- Sentiment Analysis
- Image Classification System
- Face Mask Detection
- Recommendation System
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 1000 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
Course Highlights
Through hands-on projects and real-world case studies, learners will gain practical experience in developing predictive models, image classification systems, recommendation engines, and AI-powered applications.
. By the end of the course, participants will have the skills required to design, train, evaluate, and deploy machine learning and deep learning models, preparing them for rewarding careers in AI and data science in **Offenbach**. The **Machine Learning & Deep Learning** course in **Offenbach** is a comprehensive program designed for students, software developers, and aspiring AI professionals who want to build intelligent systems using modern machine learning and deep learning techniques. The course covers Python programming, data preprocessing, supervised and unsupervised learning, neural networks, TensorFlow, Keras, computer vision, natural language processing (NLP), and model deployment. 
