- Machine Learning & Deep Learning in Practice
Accredited by Averest
350 Learners
ADVANCED
Machine Learning & Deep Learning in Practice is an applied, hands-on program designed to equip professionals with the skills required to design, build, deploy, and monitor machine learning and deep learning systems in real enterprise environments.
Accreditation With .
- Machine Learning & Deep Learning in Practice Overview
This course focuses on practical implementation, model optimization, deployment strategies, and production-level considerations.
What You Will Learn ?
- Understand the full machine learning lifecycle
- Build supervised and unsupervised learning models
- Apply deep learning architectures to real use cases
- Optimize models for performance and scalability
- Deploy ML models into production environments
- Implement MLOps best practices
- Monitor model performance and drift
- Address practical challenges in real-world ML systems
Course Key Features
- Practical hands-on exercises
- Real-world datasets
- Industry case studies
- MLOps best practices
- Deployment workflow examples
- Performance optimization techniques
- Enterprise scalability considerations
- Applied AI problem-solving labs
Training Options
In Class
- Full ML project build from start to deployment
- Deep learning lab exercises
- Team-based model optimization challenges
- Production deployment simulations
- Performance benchmarking session
Online Instructor- Led
- Guided coding sessions
- Interactive model-building exercises
- Real-time debugging workshops
- Model evaluation labs
- Live Q&A
Corporate Training
- A highly customized Corporate Training service designed exclusively for corporate employees and teams. Our training programs are meticulously planned and executed to fill knowledge and experience gaps, helping organizations achieve their business goals. With a comprehensive assessment and tailored curriculum, our experienced trainers deliver modules in areas of accreditation requirements as well as complementary practices such as leadership, communication, and technology adoption. Official certification exam voucher is provided upon completion, ensuring professional growth and measurable results. Contact us now to partner with Averest Training in order to bridge the gaps in your workforce and unlock the full potential of your team.
Schedules
Filters:
2026-May
04 - 08
Singapore, SG Singapore, Singapore
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Jun
01 - 05
London, GB London, United Kingdom
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Jun
08 - 12
Dubai, UAE Dubai, United Arab Emirates
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Jul
13 - 17
Singapore, SG Singapore, Singapore
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Aug
03 - 07
London, GB London, United Kingdom
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Aug
10 - 14
Dubai, UAE Dubai, United Arab Emirates
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Sep
14 - 18
Singapore, SG Singapore, Singapore
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Oct
12 - 16
London, GB London, United Kingdom
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Oct
19 - 23
Dubai, UAE Dubai, United Arab Emirates
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Nov
09 - 13
Dubai, UAE Dubai, United Arab Emirates
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Nov
23 - 27
Singapore, SG Singapore, Singapore
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Dec
07 - 11
London, GB London, United Kingdom
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
2026-Dec
14 - 18
Dubai, UAE Dubai, United Arab Emirates
5 Days,
09:00 - 13:00,UTC +03:00,
$ 5800.00
$ 5900.00
- Machine Learning & Deep Learning in Practice Training Cirriculum
Eligibility .
• Data Scientists
• AI Engineers
• ML Engineers
• Software Developers
• Analytics Professionals
• Technical Architects
• Advanced Business Analysts
Pre-requisites .
• Basic programming knowledge (preferably Python)
• Understanding of statistics fundamentals
• Familiarity with data handling and analysis
- Machine Learning & Deep Learning in Practice Course Content .
+
Module 1 : Machine Learning Foundations.- Types of machine learning
- ML workflow and lifecycle
- Data preprocessing and cleaning
- Feature engineering
- Model evaluation metrics
+
Module 2 : Supervised Learning in Practice.- Linear and logistic regression
- Decision trees and random forests
- Support vector machines
- Gradient boosting
- Model tuning and cross-validation
+
Module 3 : Unsupervised Learning.- Clustering techniques (K-means, hierarchical)
- Dimensionality reduction (PCA)
- Anomaly detection
- Real-world use cases
+
Module 4 : Deep Learning Fundamentals.- Neural networks basics
- Backpropagation
- Activation functions
- Optimization techniques
- Regularization strategies
+
Module 5 : Deep Learning Architectures.- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs, LSTM)
- Transformers and attention mechanisms
- Transfer learning
- Model fine-tuning
+
Module 6 : Model Deployment & MLOps.- Model packaging and APIs
- CI/CD for ML
- Model versioning
- Monitoring model drift
- Scaling ML systems
+
Module 7 : Practical Industry Applications.- ML in finance (risk & fraud detection)
- ML in operations (predictive maintenance)
- ML in marketing (customer segmentation)
- ML in cybersecurity (threat detection)
You May Be Interested