Professional Training on Machine Learning
🤖 Professional Training on Machine Learning
Overview
Machine Learning (ML) is transforming industries by enabling systems to learn from data and make intelligent predictions without being explicitly programmed. From healthcare and finance to environmental management and engineering, machine learning is driving innovation and efficiency.
This professional training introduces participants to the principles, tools, and applications of machine learning. It combines theory with practical exercises to help participants design, train, and evaluate machine learning models for real-world challenges.
Duration
4 Days (intensive program)
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Who Should Attend
This training is designed for:
- Students and researchers in computer science, engineering, and data science
- Professionals in IT, finance, environment, business, and engineering sectors
- Development practitioners interested in applying AI/ML to sustainability and monitoring projects
- Anyone seeking to understand the fundamentals of machine learning and its applications
Learning Outcomes
By the end of this training, participants will be able to:
- Understand the foundations of machine learning and artificial intelligence.
- Apply supervised, unsupervised, and reinforcement learning techniques.
- Use popular ML tools and libraries (e.g., Python, TensorFlow, Scikit-learn).
- Prepare and process datasets for machine learning models.
- Train and evaluate models using appropriate performance metrics.
- Explore applications of ML in business, engineering, environment, and development projects.
Course Modules
Module 1: Introduction to Machine Learning
- What is ML? Key concepts and real-world applications
Module 2: Data Preparation and Processing
- Cleaning, transformation, and feature engineering
Module 3: Supervised Learning
- Regression and classification techniques
Module 4: Unsupervised Learning
- Clustering and dimensionality reduction
Module 5: Neural Networks and Deep Learning (Introductory)
- Basics of neural networks and practical use cases
Module 6: Model Evaluation and Optimization
- Accuracy, precision, recall, cross-validation, and tuning
Module 7: Applications of Machine Learning
- Case studies in health, environment, finance, and social development
Training Approach
The course is designed to be hands-on and interactive, combining:
- Expert-led sessions and tutorials
- Live coding demonstrations
- Practical exercises using real datasets
- Group work and problem-solving challenges
- Case studies showing applications of ML in different sectors
Certification
Participants will receive a Certificate of Completion issued by Daira Sabz Consulting and Engineering Group upon successful completion.
Key Information
- Format: In-person, online, or hybrid
- Duration: 4 days
- Target Audience: Students, professionals, researchers, and practitioners
- Language: English (with multilingual support where applicable)
Why This Course?
- Provides essential ML skills highly demanded in the global job market
- Focuses on practical applications across industries and development contexts
- Equips participants to apply machine learning in real projects
- Builds foundational knowledge for further study in AI and Data Science
Registration & Contact
Seats are limited and allocated on a first-come, first-served basis.
📧 Email: info@dairasabz.com
🌐 Website: www.dairasabz.com