Ai & Machine Learning For It Professionals: Driving Automation And Innovation in Kenya
Introduction:
Artificial Intelligence (AI) and Machine Learning (ML) are transforming IT operations, enabling automation, predictive analytics, and intelligent decision-making. This course on AI & Machine Learning for IT Professionals equips participants with the specialized knowledge and skills to leverage AI/ML for practical applications and automation within IT environments. Participants will learn how to build and deploy AI/ML models, integrate them with existing systems, and utilize them to enhance IT efficiency and security. This course bridges the gap between theoretical AI/ML concepts and real-world IT applications, empowering professionals to drive innovation and automation.
Target Audience:
This course is designed for IT professionals seeking to apply AI/ML to their daily work, including:
- System Administrators
- Network Engineers
- DevOps Engineers
- Security Analysts
- IT Managers
- Anyone interested in leveraging AI/ML for IT automation and innovation
Course Objectives:
Upon completion of this AI & Machine Learning for IT Professionals course, participants will be able to:
- Understand the fundamentals of AI and machine learning.
- Build and deploy practical AI/ML models for IT applications.
- Automate IT tasks using AI/ML techniques.
- Utilize AI/ML for predictive analytics and anomaly detection.
- Integrate AI/ML with existing IT systems and tools.
- Understand the ethical considerations of AI/ML in IT.
- Apply AI/ML for network monitoring and security.
- Utilize AI/ML for IT service management and automation.
- Develop strategies for implementing AI/ML in IT environments.
- Understand the importance of data management for AI/ML.
- Enhance their ability to leverage AI/ML for IT automation and innovation.
- Improve their organization's IT efficiency and security using AI/ML.
- Contribute to improved IT operations and decision-making within their organization.
- Stay up-to-date with the latest trends and best practices in AI/ML for IT.
- Become a more knowledgeable and effective IT professional in the age of AI.
- Understand ethical considerations in AI/ML deployment within IT.
- Learn how to use AI/ML tools and platforms effectively for IT tasks.
DURATION
10 Days
COURSE CONTENT
Module 1: Introduction to AI and Machine Learning for IT
- Understanding the fundamentals of AI, ML, and deep learning.
- The relevance of AI/ML in modern IT environments.
- Key AI/ML concepts and terminology for IT professionals.
- Overview of practical AI/ML applications in IT.
- Setting up the development environment and tools.
Module 2: Data Collection and Preprocessing for IT Applications
- Identifying relevant data sources for IT applications (logs, metrics, etc.).
- Data collection and extraction techniques.
- Data cleaning and preprocessing methods.
- Feature engineering for IT-related datasets.
- Data storage and management for AI/ML projects.
Module 3: Machine Learning Fundamentals with Python for IT
- Introduction to Python libraries for ML (Scikit-learn, Pandas, NumPy).
- Supervised learning algorithms (classification, regression).
- Unsupervised learning algorithms (clustering, dimensionality reduction).
- Model evaluation and selection 1 techniques.
- Hands-on exercises with IT-related datasets.
Module 4: Predictive Analytics for IT Operations
- Predicting system failures and performance degradation.
- Capacity planning and resource optimization.
- Anomaly detection and trend analysis.
- Time-series forecasting for IT metrics.
- Building predictive models for IT infrastructure.
Module 5: AI-Driven Network Monitoring and Security
- Network traffic analysis using ML.
- Intrusion detection and prevention using AI.
- Anomaly detection in network behavior.
- Predicting network outages and bottlenecks.
- Automating network security tasks with AI.
Module 6: AI for IT Service Management (ITSM) Automation
- Automating incident classification and routing.
- Building AI-powered chatbots for IT support.
- Knowledge base automation and search.
- Predictive maintenance and problem resolution.
- Automating IT service requests and workflows.
Module 7: Log Analysis and Anomaly Detection with ML
- Log aggregation and parsing techniques.
- Identifying anomalies in log data using ML algorithms.
- Detecting security threats and suspicious activity in logs.
- Automating log analysis and alerting.
- Building custom log analysis tools.
Module 8: Deep Learning for IT Applications
- Introduction to deep learning concepts and frameworks (TensorFlow, Keras, PyTorch).
- Neural network architectures for IT tasks.
- Deep learning for image and video analysis (e.g., security cameras).
- Deep learning for natural language processing (e.g., log analysis).
- Building and training deep learning models for IT.
Module 9: AI for Cloud Infrastructure Management
- Automating cloud resource provisioning and scaling.
- Predicting cloud resource utilization and costs.
- Optimizing cloud security and compliance.
- Automating cloud infrastructure monitoring and alerting.
- Building AI-powered cloud management tools.
Module 10: AI for DevOps and Automation
- Automating software deployment and testing.
- Utilizing AI for code analysis and quality assurance.
- Automating infrastructure configuration and management.
- Building AI-powered CI/CD pipelines.
- Utilizing AI for performance monitoring and optimization.
Module 11: Integrating AI/ML with Existing IT Systems and Tools
- API integration and data exchange.
- Building custom AI/ML integrations.
- Utilizing existing AI/ML platforms and services.
- Deploying AI/ML models in production environments.
- Monitoring and maintaining AI/ML systems.
Module 12: Ethical Considerations and Responsible AI in IT
- Understanding the ethical implications of AI/ML in IT.
- Addressing bias and fairness in AI/ML models.
- Ensuring data privacy and security.
- Developing responsible AI/ML practices.
- Understanding legal and regulatory requirements.
Module 13: Building and Deploying AI/ML Models in Production
- Model deployment strategies and best practices.
- Utilizing containerization and orchestration for model deployment.
- Monitoring model performance and drift.
- Continuous integration and continuous deployment (CI/CD) for AI/ML models.
- Scaling and optimizing AI/ML systems.
Module 14: AI/ML Project Management and Implementation
- Developing AI/ML project plans and roadmaps.
- Managing AI/ML projects and teams.
- Communicating AI/ML project results and insights.
- Measuring the ROI of AI/ML projects.
- Building a culture of AI/ML innovation in IT.
Module 15: Emerging Trends and Future of AI/ML in IT
- Exploring emerging AI/ML technologies and applications.
- Understanding the impact of AI/ML on the future of IT.
- Developing strategies for adapting to evolving AI/ML landscapes.
- Continuous learning and professional development in AI/ML.
- The impact of Generative AI on IT workflows.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Training Venue
The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.
Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 5 working days before commencement of the training.
| Dates | Fees | Location | Apply |
|---|---|---|---|
| 07/07/2025 - 18/07/2025 | $3000 | Nairobi |
|
| 14/07/2025 - 25/07/2025 | $5500 | Johannesburg |
|
| 14/07/2025 - 25/07/2025 | $3000 | Nairobi |
|
| 04/08/2025 - 15/08/2025 | $3000 | Nairobi |
|
| 11/08/2025 - 22/08/2025 | $3500 | Mombasa |
|
| 18/08/2025 - 29/08/2025 | $3000 | Nairobi |
|
| 01/09/2025 - 12/09/2025 | $3000 | Nairobi |
|
| 08/09/2025 - 19/09/2025 | $4500 | Dar es Salaam |
|
| 15/09/2025 - 26/09/2025 | $3000 | Nairobi |
|
| 06/10/2025 - 17/10/2025 | $3000 | Nairobi |
|
| 13/10/2025 - 24/10/2025 | $4500 | Kigali |
|
| 20/10/2025 - 31/10/2025 | $3000 | Nairobi |
|
| 03/11/2025 - 14/11/2025 | $3000 | Nairobi |
|
| 10/11/2025 - 21/11/2025 | $3500 | Mombasa |
|
| 17/11/2025 - 28/11/2025 | $3000 | Nairobi |
|
| 01/12/2025 - 12/12/2025 | $3000 | Nairobi |
|
| 08/12/2025 - 19/12/2025 | $3000 | Nairobi |
|
| 05/01/2026 - 16/01/2026 | $3000 | Nairobi, Kenya |
|
| 12/01/2026 - 23/01/2026 | $3000 | Nairobi, Kenya |
|
| 19/01/2026 - 30/01/2026 | $3000 | Nairobi, Kenya |
|
| 02/02/2026 - 13/02/2026 | $3000 | Nairobi, Kenya |
|
| 09/02/2026 - 20/02/2026 | $3000 | Nairobi, Kenya |
|
| 16/02/2026 - 27/02/2026 | $3000 | Nairobi, Kenya |
|
| 02/03/2026 - 13/03/2026 | $3000 | Nairobi, Kenya |
|
| 09/03/2026 - 20/03/2026 | $4500 | Kigali, Kenya |
|
| 16/03/2026 - 27/03/2026 | $3000 | Nairobi, Kenya |
|
| 06/04/2026 - 17/04/2026 | $3000 | Nairobi, Kenya |
|
| 13/04/2026 - 24/04/2026 | $3500 | Mombasa, Kenya |
|
| 13/04/2026 - 24/04/2026 | $3000 | Nairobi, Kenya |
|
| 04/05/2026 - 15/05/2026 | $3000 | Nairobi, Kenya |
|
| 11/05/2026 - 22/05/2026 | $5500 | Dubai, UAE |
|
| 18/05/2026 - 29/05/2026 | $3000 | Nairobi, Kenya |
|