course | Advanced Machine Learning Applications
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DIGTR-1507 | Advanced Machine Learning Applications
Course Sector : Digital Transformation and Innovation
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 2025-06-16 | 2025-06-20 | Galway | $4,950 | Book now |
| 5 Days | 2025-09-29 | 2025-10-03 | Dubai | $4,250 | Book now |
| 5 Days | 2025-12-14 | 2025-12-18 | El Doha | $4,250 | Book now |
Course Introduction
This 5-day training course explores advanced machine learning (ML) techniques and their real-world applications across industries. Participants will gain hands-on experience with cutting-edge ML models, deep learning architectures, and AI-driven decision-making. The course covers key topics such as natural language processing (NLP), computer vision, reinforcement learning, and model optimization. By the end, participants will be equipped to develop, deploy, and optimize ML solutions for complex business challenges.
Course objective
- Understand advanced ML techniques and their industry applications.
- Implement deep learning models for tasks such as image recognition and NLP.
- Optimize ML models for performance, scalability, and accuracy.
- Explore reinforcement learning and its role in automation and AI decision-making.
- Apply AI-driven predictive analytics for data-driven business strategies.
- Address ethical considerations, bias, and model interpretability.
- Gain practical experience through hands-on coding, case studies, and real-world projects.
Course Outline | Day 01
Foundations of Advanced Machine Learning
- Overview of supervised, unsupervised, and reinforcement learning
- Deep learning architectures: CNNs, RNNs, Transformers
- Tools and frameworks: TensorFlow, PyTorch, Scikit-Learn
- Data preprocessing and feature engineering
Course Outline | Day 02
Natural Language Processing (NLP) & Text Analytics
- Word embeddings (Word2Vec, GloVe, BERT, GPT)
- Text classification, sentiment analysis, and chatbots
- Advanced NLP applications: speech recognition and translation
Course Outline | Day 03
Computer Vision & Image Processing
- Convolutional Neural Networks (CNNs) and object detection
- Image segmentation and facial recognition applications
- Transfer learning and pre-trained model fine-tuning
Course Outline | Day 04
Reinforcement Learning & Model Optimization
- Fundamentals of reinforcement learning and reward-based learning
- Model tuning, hyperparameter optimization, and performance evaluation
- Explainability and fairness in ML models
Course Outline | Day 05
Real-World Applications & Deployment
- Deploying ML models using cloud platforms and edge computing
- Future trends in AI, AutoML, and federated learning
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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