An Intensive 5-day Training Course

Certified Artificial Intelligence Practitioner

INTRODUCTION TO THE COURSE

The Certified Artificial Intelligence Practitioner training course (CAIP) offered by KC Academy is a comprehensive training course designed to equip participants with the necessary skills and knowledge to implement artificial intelligence (AI) and machine learning (ML) solutions in a business context. Throughout this training course, participants will engage in developing actionable insights and innovative solutions by applying AI and ML to real-world business problems. The training course is structured to follow a methodical workflow for developing data-driven solutions, ensuring that attendees can not only grasp but also apply these approaches to optimize and enhance business operations.

Ideal for software developers, IT professionals, and business analysts aiming to expand their expertise in artificial intelligence, the Certified Artificial Intelligence Practitioner training course focuses on the practical application of building, evaluating, and maintaining AI models. Attendees will delve into various topics such as data preparation, linear regression, forecasting models, classification models, and more sophisticated techniques like support-vector machines and neural networks. By the end of this course, individuals will be well-prepared to sit for the CertNexus Certified AI Practitioner Exam, solidifying their credentials as experts in the AI field and significantly enhancing their professional capability to contribute to their organizations' success in the evolving technological landscape.

Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This Certified Artificial Intelligence Practitioner (CAIP) training course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions.

COURSE DETAILS

Objectives Icon

OBJECTIVES

At the end of this Certified Artificial Intelligence Practitioner(CAIP) training course, you will develop AI solutions for business problems. You will:

  • Solve a given business problem using AI and ML.
  • Prepare data for use in machine learning.
  • Train, evaluate, and tune a machine learning model.
  • Build linear regression models.
  • Build forecasting models.
  • Build classification models using logistic regression and k -nearest neighbor.
  • Build clustering models.
  • Build classification and regression models using decision trees and random forests.
  • Build classification and regression models using support-vector machines (SVMs).
  • Build artificial neural networks for deep learning.
  • Put machine learning models into operation using automated processes.
  • Maintain machine learning pipelines and models while they are in production.
Personal Impact Icon

PERSONAL IMPACT

By attending this Certified Artificial Intelligence Practitioner training course, participants will be able to:

  • Boosts professional value through validated AI proficiency, enhancing career prospects and advancement opportunities.
  • Expand their technical abilities in AI and machine learning, opening up new job opportunities and enabling the undertaking of complex projects.
  • Enhance problem-solving and critical thinking skills by teaching individuals to address complex challenges with AI-driven solutions effectively.
  • Make valuable networking opportunities with AI professionals, facilitating collaboration, mentorship, and potential job offers.
Target Audience Icon

WHO SHOULD ATTEND?

The skills covered in this training course converge on four areas—software development, IT operations, applied math and statistics, and business analysis. Target participants for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems.

So, the target participant is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decision-making products that bring value to the business.

A typical participant in this training course should have several years of experience with computing technology, including some aptitude in computer programming.

This Certified Artificial Intelligence Practitioner(CAIP) training course is also designed to assist participants in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification.

DAILY AGENDA

Day 1: Solving Business Problems Using AI and ML
  • Identify AI and ML solutions for business problems
  • Formulate a machine learning problem
  • Select approaches to machine learning

Preparing Data

  • Collect data
  • Transform data
  • Engineer features
  • Work with unstructured data
Day 2: Training, Evaluating, and Tuning a Machine Learning Model
  • Train a machine learning model
  • Evaluate and tune a machine learning model

Building Linear Regression Models

  • Build regression models using linear algebra
  • Build regularized linear regression models
  • Build iterative linear regression models

Building Forecasting Models

  • Build univariate time series models
  • Build multivariate time series models
Day 3: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
  • Train binary classification models using logistic regression
  • Train binary classification models using k-nearest neighbor
  • Train multi-class classification models
  • Evaluate classification models
  • Tune classification models

Building Clustering Models

  • Build k-means clustering models
  • Build hierarchical clustering models

Building Decision Trees and Random Forests

  • Build decision tree models
  • Build random forest models
Day 4: Building Support-Vector Machines
  • Build SVM models for classification
  • Build SVM models for regression

Building Artificial Neural Networks

  • Build Multi-Layer Perceptrons (MLP)
  • Build Convolutional Neural Networks (CNN)
  • Build Recurrent Neural Networks (RNN)
Day 5: Operationalizing Machine Learning Models
  • Deploy machine learning models
  • Automate the machine learning process with MLOps
  • Integrate models into machine learning systems

Maintaining Machine Learning Operations

  • Secure machine learning pipelines
  • Maintain models in production
Objectives Icon

Certificate

On successful completion of this training course, KC ACademy Certificate will be awarded to the delegates.

RELATED CATEGORIES

OTHER TRAINING COURSES

YOU MIGHT BE INTERESTED AS WELL…

CLASSROOM

Hybrid Human-Artificial Intelligence (HHAI)

14-18 Jul 2025
Boston, USA
CLASSROOM

Artificial Intelligence (AI), Business and the Future of Work

14-18 Jul 2025
Dubai, UAE
CLASSROOM

Artificial Intelligence (AI) in Contract and Project Management

18-29 Aug 2025
London, United Kingdom
CLASSROOM

Artificial Intelligence (AI) in Project Management

30 Jun-04 Jul 2025
Amsterdam, The Netherlands
CLASSROOM

Artificial Intelligence (AI) in Contract Management

30 Jun-04 Jul 2025
Amsterdam, The Netherlands
CLASSROOM

The Tech-Savvy Administrator: Incorporating AI for Efficiency and Innovation

23-27 Jun 2025
Dubai, UAE
CLASSROOM

AI in Digital Marketing

07-11 Jul 2025
Dubai, UAE
CLASSROOM

Mastering AI-Powered Content Creation

04-08 Aug 2025
Dubai, UAE
CLASSROOM

AI for Quality Control and Assurance

18-22 Aug 2025
London, United Kingdom
ONLINE

Artificial Intelligence (AI) in Procurement and Supply Chain Management

26-30 May 2025
Online

FREQUENTLY ASKED QUESTIONS

This FAQ section provides quick answers to the most common questions about our services, procedures, and policies. We aim to make your experience with us as straightforward as possible. For further assistance, our support team is ready to help.

Are there prerequisites or language requirements? +
How many students are in a course? Who will be my classmates? +
Do I need specific equipment to take Online Courses? +
How can I register? +

READY TO GET STARTED?

Connect with our team to learn more about our customised learning and development solutions.

SUBSCRIBE TO OUR NEWSLETTER

Stay up to date with our latest insights on leadership, strategy and other topics that are relevant to your business. No spam, great content.