Artificial Intelligence and Machine Learning in Practice Course
Are you ready to dive into the revolutionary world of Artificial Intelligence (AI) and Machine Learning (ML)? Imagine transforming vast amounts of data into actionable insights, developing intelligent systems that can predict future trends, and automating complex tasks with ease. At Trainingcred, we understand the transformative power of AI and ML in today's tech-driven world. Our Artificial Intelligence and Machine Learning in Practice Training Course is designed to equip you with the skills and knowledge to harness these technologies effectively. Let’s explore how you can become a leader in the AI and ML revolution!
In-Person: Classroom Sessions
| Location | Duration | Language | |
|---|---|---|---|
| Nairobi, Kenya | 10 Days | English | View Dates & Pricing |
| Kigali, Rwanda | 10 Days | English | View Dates & Pricing |
| Kampala, Uganda | 10 Days | English | View Dates & Pricing |
| Dubai, United Arab Emirates (UAE) | 10 Days | English | View Dates & Pricing |
| Mombasa, Kenya | 10 Days | English | View Dates & Pricing |
| Naivasha, Kenya | 10 Days | English | View Dates & Pricing |
| Nakuru, Kenya | 10 Days | English | View Dates & Pricing |
| Kisumu, Kenya | 10 Days | English | View Dates & Pricing |
Virtual (Zoom) Instructor-Led
| Code | Start Date | End Date | Fee | |
|---|---|---|---|---|
| AI-ML | Oct 14, 2024 | Oct 25, 2024 | USD 1500 | Register Register Group |
| AI-ML | Nov 18, 2024 | Nov 29, 2024 | USD 1500 | Register Register Group |
| AI-ML | Dec 23, 2024 | Jan 03, 2025 | USD 1500 | Register Register Group |
| AI-ML | Jan 06, 2025 | Jan 17, 2025 | USD 1500 | Register Register Group |
| AI-ML | Feb 03, 2025 | Feb 14, 2025 | USD 1500 | Register Register Group |
In-House Training
Transform Your Workforce
Learn emerging skills quickly with custom curriculum designed as per your needs.
Why top organizations prefer Trainingcred
- High engagement and outcome-centric learning
- Customized curriculum built with industry leaders, for industry leaders
- Hands-on exercises and industry use cases
- Strong reporting to track learning and calculate training ROI for managers
- Day 1 production ready on the completion of the training
Programs delivered as per your training needs
On Premises
Virtual Instructor-Led
Self-Paced
Blended
Modules Covered, Designed by Experts
Module 1: Introduction to AI and ML
- Overview of AI and ML
- Historical Evolution and Future Trends
- Key Terminologies and Concepts
- Ethical Considerations in AI and ML
Module 2: Data Preprocessing and Feature Engineering
- Data Collection and Cleaning
- Handling Missing Data
- Feature Selection and Extraction
- Data Normalization and Transformation
Module 3: Supervised Learning Algorithms
- Linear and Logistic Regression
- Decision Trees and Random Forests
- Support Vector Machines
- Model Evaluation and Validation
Module 4: Unsupervised Learning Algorithms
- Clustering Techniques (K-means, Hierarchical)
- Dimensionality Reduction (PCA, LDA)
- Anomaly Detection
- Association Rule Learning
Module 5: Neural Networks and Deep Learning
- Introduction to Neural Networks
- Deep Learning Architectures (CNN, RNN)
- Training Deep Learning Models
- Applications of Deep Learning
Module 6: Natural Language Processing (NLP)
- Text Processing and Tokenization
- Sentiment Analysis
- Language Models and Transformers
- Chatbots and Conversational AI
Module 7: Computer Vision
- Image Processing Fundamentals
- Object Detection and Recognition
- Convolutional Neural Networks (CNNs)
- Image Segmentation Techniques
Module 8: Reinforcement Learning
- Fundamentals of Reinforcement Learning
- Markov Decision Processes
- Q-Learning and Policy Gradients
- Applications of Reinforcement Learning
Module 9: AI and ML Tools and Frameworks
- Introduction to Python for AI and ML
- Using TensorFlow and Keras
- Exploring PyTorch and Scikit-Learn
- Overview of Cloud-Based AI Services
Module 10: Deploying AI and ML Models
- Model Deployment Strategies
- Serving Models with APIs
- Monitoring and Maintaining Models
- Case Studies of Deployed AI Systems
Module 11: AI and ML in Business Applications
- AI in Healthcare
- AI in Finance
- AI in Marketing and Sales
- AI in Manufacturing and Supply Chain
About the Course
The fields of AI and ML are rapidly evolving, offering immense opportunities for innovation and efficiency. This course provides a comprehensive overview of AI and ML, focusing on practical applications and real-world case studies. You will learn how to develop, implement, and manage AI and ML projects, leveraging the latest tools and techniques to solve complex problems. Through hands-on exercises, interactive sessions, and expert guidance, you will gain the confidence to apply AI and ML in various business contexts.
The goal of this course is to give delegates practical experience using ML and AI techniques to solve challenging problems. The complete lifecycle of AI and ML projects, from data preprocessing to model deployment, will be covered by means of a blend of theory, case studies, and hands-on exercises. You will learn how to assess model performance, acquire understanding of various algorithms, and identify best practices for incorporating AI and ML into current systems.
Target Audience
This course is ideal for:
- Data scientists and analysts
- Software developers and engineers
- IT professionals and system architects
- Business intelligence professionals
- Tech enthusiasts and innovators
Course Objectives
- Understand the core concepts of AI and ML.
- Develop practical skills in building and deploying AI and ML models.
- Learn to use popular AI and ML tools and frameworks.
- Apply AI and ML techniques to real-world problems.
- Enhance your ability to make data-driven decisions.
Organizational and Professional Benefits
Professional Benefits:
- Enhance your career prospects with advanced AI and ML skills.
- Gain practical experience in using cutting-edge technologies.
- Improve your problem-solving and analytical abilities.
- Increase your value to employers by mastering in-demand skills.
- Join a network of professionals and experts in the field.
Organizational Benefits:
- Drive innovation and efficiency through AI and ML.
- Improve decision-making with data-driven insights.
- Automate complex tasks and processes, reducing operational costs.
- Stay ahead of the competition with advanced technological capabilities.
- Foster a culture of continuous learning and technological adoption.
Training Methodology
Our training methodology is designed to be engaging, interactive, and practical. It includes:
- Instructor-led sessions with industry experts.
- Interactive workshops and group activities.
- Real-world case studies and scenario-based learning.
- Hands-on projects and exercises.
Upcoming Sessions in International Locations
Certification: Your Badge of Honor!
Upon successful completion of our Artificial Intelligence and Machine Learning in Practice Course, you won't just walk away with newfound knowledge – you'll also snag a Trainingcred Certificate! This is your golden ticket, showcasing your expertise and dedication in Computing and Information Technology.
Tailor-Made Course: Like a Suit, But for Your Brain!
Imagine Artificial Intelligence and Machine Learning in Practice Course that fits your team's needs as perfectly as a tailor-made suit! That's what we offer with our bespoke training solution. We don't believe in one-size-fits-all; instead, we're all about crafting a learning experience that's as unique as your organization.
How do we do it? By diving deep with a Training Needs Assessment, we uncover the hidden gems – the skills your team already rocks at, the knowledge gaps we need to bridge, and the ambitions soaring in their minds. It's not just training; it's a transformation journey, meticulously designed just for you and your team. Let's make learning personal.
Accommodation and Airport Pickup
We’re here to make your experience seamless! If you need accommodation or airport pickup, just let us know. To arrange your reservations, please reach out to our Training Officer:
- Email: [email protected]
- Call/WhatsApp: +254759509615
We’re happy to assist!
Frequently Asked Questions
No worries at all. We all find ourselves with questions now and then.
What is artificial intelligence (AI)?
Artificial intelligence is the term used to describe the imitation of human intelligence in machines that are designed to think and perform human functions like decision-making, learning, and problem-solving.
What is machine learning (ML)?
Machine learning is a subset of AI that enables systems to learn from data and improve performance without being explicitly programmed. Its main goal is to create algorithms that are able to learn from data and make inferences or predictions from it.
How are artificial intelligence and machine learning used in practice?
Artificial intelligence can help manufacturing leaders automate their business processes by applying data analytics and machine learning to applications such as the following; Identifying equipment errors before malfunctions occur using the internet of the things (IoT), analytics, and machine learning.
What`s the difference between AI and ML?
AI includes everything from smart assistance like Alexa to robotic vacuum cleaners and self-driving cars. Machine learning (ML) is one among many other branches of AI. ML is the science of developing algorithms and statistical models that computer system use to perform complex tasks without explicit instructions.
What are the challenges of implementing machine learning in real-world applications?
Acquiring labeled data for training, handling problems with data quality and preprocessing, choosing the appropriate model and adjusting hyperparameters, comprehending the interpretability of intricate models (like deep learning), and implementing and maintaining models in real-world settings are some of the challenges.
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