EXIN BCS Machine Learning Award 1 Day Training in Sugar Land, TX
Overview
Certificate: Upon Completion of Exam
Language: English
Duration: 1 Day
Credits: 8
Course Delivery: Classroom
Refreshments: Snacks, Beverages and Lunch included in a classroom session
Course Overview:
The term ‘machine learning’ has increased in popularity in the last decade and is a technology which is becoming more commonly used within many organizations. With its ability to help solve business problems and develop new customer experiences, there is now a greater demand for individuals with the knowledge and skills to support organizations to successfully implement the technology to deliver improvements.
The EXIN BCS Machine Learning Award is designed for individuals wishing to gain an understanding of the principles of machine learning and the process through which it can be developed. This award explores what machine learning is and how it is used in practice. It provides an introduction into the different types of machine learning and the tools and techniques required to develop it, including a basic introduction to algorithms. This award will enable candidates to understand these concepts at a foundation level, enabling them to be better informed and equipping them with knowledge which they can build upon through further study and application.
Main Subjects:
- Introduction to Machine Learning
- Programming in Machine Learning
- Machine Learning Algorithms
- Practical Applications of Machine Learning
Learning Objectives:
Machine learning is revolutionizing industries, powering fraud detection, personalized recommendations, and AI-driven automation—but how does it actually work?
The EXIN BCS Machine Learning Award is designed to give you a solid foundation in ML principles, coding, algorithms, and real-world applications—without requiring deep technical expertise.
Here’s why this certification is essential for you:
- Learn what machine learning is, how it works, and its role within AI.
- Get insights into neural networks, regression, classification, clustering, and deep learning, and understand how they solve real-world problems.
- Understand how to collect, preprocess, and transform data for machine learning models, ensuring better accuracy and performance.
- Get sweeping knowledge across recommendation engines (e.g. Netflix, Spotify) to object recognition, prediction, and automation, and explore how ML is used in business globally.
- Become familiar with programming languages & ML frameworks such as Python, TensorFlow, Scikit-Learn, even if you have little programming experience.
- Learn how ML models are trained, tested, fine-tuned, and deployed in real-world scenarios.
- Understand the limitations, biases, and ethical considerations when implementing machine learning solutions.
Who is this certification for?
IT Professionals, Software Developers, Data Analysts, Data Scientists, Business Leaders & AI Strategists, Project Managers, Product Managers, Engineers & Technical Consultants, Individuals with an interest in AI and a background in science, engineering, knowledge engineering, finance, education, or IT services
Requirements for Certification:
Successful completion of the EXIN BCS Machine Learning Award exam.
Examination Details
- Examination type: Multiple-choice questions
- Number of questions: 18, of which 2 scenario-based questions worth 2 points each
- Pass mark: 65% (13/20 points)
- Open book: No
- Notes: No
- Electronic equipment/aides permitted: No
- Exam duration: 30 minutes
The Rules and Regulations for EXIN’s examinations apply to this exam.
Required reading
The knowledge required for the exam is covered in the following literature:
1. Aurélien Géron Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems O’Reilly (2022) ISBN: 978-1098125974 (hard copy)
2. Oliver Theobald Machine Learning for Absolute Beginners: A Plain English Introduction Independently published (3 rd edition, 2021) ISBN: 979-8558098426
3. Gilbert Strang Linear Algebra and Learning from Data Wellesley-Cambridge Press (1 st edition, 2019) ISBN: 978-0692196380 (Hard copy)
4. Andrew Lowe, Steve Lawless Artificial Intelligence and Machine Learning Foundations: Learning From Experience BCS (2024) ISBN: 978-1780176734
5. Sarah Burnett AI in Business: Towards the Autonomous Enterprise BCS (2024) ISBN: 978-1780176673
How does the BCS Machine Learning Award Prepare for the Future of Work?
- Master the Foundations of AI and Machine Learning: Build a strong understanding of algorithms, neural networks, and model training as essential skills for today’s AI-driven world.
- Bridge the Gap Between Business and Technology: Discover how machine learning is applied in fraud detection, automation, and data-driven decision-making across industries.
- Gain Hands-On Exposure Without a Coding Background: Work with tools like Python, TensorFlow, and Scikit-Learn even if you don’t have prior programming experience.
- Get Future-Ready for AI Career Opportunities: Develop industry-relevant skills, terminology, and frameworks to thrive in AI and data science roles.
- Build a Responsible AI Mindset: Understand ethics, bias, and responsible use of AI in real-world scenarios.
- Earn a Globally Recognized Certification: Boost your career with a respected credential that’s valued across IT, finance, consulting, and more.
- Explore Deep Learning and Intelligent Systems: Learn how adaptive learning agents and neural networks power modern AI applications.
- Understand the Role of Data in Machine Learning: Gain insight into how data is collected, prepared, and used to train machine learning models effectively.
- Evaluate Industry-Standard ML Tools: Familiarize yourself with popular open-source and commercial platforms used in machine learning today.
"This content and material is developed and owned by Mangates Tech Solutions, accredited by EXIN for delivering certified training programs."
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Highlights
- 8 hours
- In person
Refund Policy
Location
Regus - Sugar Land - Town Square
2245 Texas Drive Suite 300
PH: +1 469 666 9332 Sugar Land, TX 77479
How do you want to get there?
Introduction to Machine Learning
● Definition and Overview ● Applications of Machine Learning ● Role of Learning Agents ● Concept of Deep Learning ● Purpose and Function of Neural Networks ● Integration with Knowledge-Based Systems ● Data Interaction in Machine Learning
Programming in Machine Learning
● Programming Languages for Machine Learning ● Software Tools: Open Source vs. Proprietary
Machine Learning Algorithms
● Mathematical Foundations ● Common Algorithms in Machine Learning ● Types of Learning: Supervised, Unsupervised, and Semi-Supervised
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