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CertNexus - Certified Artificial Intelligence Practitioner
Overview
This accelerated Certified Artificial Intelligence Practitioner™ (CAIP) course, is an in-demand, fast-growing training program and certification designed for data practitioners desiring to get equipped with vendor-neutral, cross-industry knowledge of Artificial Intelligence (AI) concepts and skills. It enables you to select, train, and implement Machine Learning solutions.
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 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.
The Certified Artificial Intelligence Practitioner™ (CAIP) has emerged as the industry standard for those desiring to confirm their AI and ML skills.
To be an effective Machine Learning Practitioner, you require hands-on practice. CertNexus CAIP training covers artificial intelligence concepts while providing ample opportunities to practice the required skills of a ML professional.
In just 4 days, you’ll learn to develop AI solutions for business problems. You’ll also learn how to:
- 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 neighbour.
- 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.
At the end of this course, you’ll sit the CertNexus exam, and achieve your Certified Artificial Intelligence Practitioner™ (CAIP) certification. Through Firebrand’s Lecture | Lab | Review methodology, you’ll get certified at twice the speed of the traditional training and get access to courseware, learn from certified instructors, and train in a distraction-free environment.
Audience
This course is ideal for:
- Practitioners who are seeking to demonstrate a vendor neutral, cross-industry skill set within AI and with a focus on ML that will enable them to design, implement, and hand off an AI solution or environment.
- Those 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.
- 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.
Benefits
Other accelerated training providers rely heavily on lecture and independent self-testing and study.
Effective technical instruction must be highly varied and interactive to keep attention levels high, promote camaraderie and teamwork between the students and instructor, and solidify knowledge through hands-on learning.
Firebrand Training provides instruction to meet every learning need:
- Intensive group instruction
- One-on-one instruction attention
- Hands-on labs
- Lab partner and group exercises
- Question and answer drills
- Independent study
Curriculum
- Module 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
- Module 2: Preparing Data
- Collect Data
- Transform Data
- Engineer Features Topic D: Work with Unstructured Data
- Module 3: Training, Evaluating, and Tuning a Machine Learning Model
- Topic A: Train a Machine Learning Model
- Topic B: Evaluate and Tune a Machine Learning Model
- Module 4: Building Linear Regression Models
- Build Regression Models Using Linear Algebra
- Build Regularized Linear Regression Models
- Build Iterative Linear Regression Models
- Module 5: Building Forecasting Models
- Topic A: Build Univariate Time Series Models
- Topic B: Build Multivariate Time Series Models
- Module 6: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
- Train Binary Classification Models Using Logistic Regression
- Train Binary Classification Models Using k-Nearest Neighbour
- Train Multi-Class Classification Models
- Evaluate Classification Models Topic E: Tune Classification Models
- Module 7: Building Clustering Models
- Build k-Means Clustering Models
- Build Hierarchical Clustering Models
- Module 8: Building Decision Trees and Random Forests
- Build Decision Tree Models
- Build Random Forest Models
- Module 9: Building Support-Vector Machines
- Build SVM Models for Classification
- Build SVM Models for Regression
- Module 10: Building Artificial Neural Networks
- Build Multi-Layer Perceptrons (MLP)
- Build Convolutional Neural Networks (CNN)
- Build Recurrent Neural Networks (RNN)
- Module 11: Operationalizing Machine Learning Models
- Deploy Machine Learning Models
- Automate the Machine Learning Process with MLOps
- Integrate Models into Machine Learning Systems
- Module 12: Maintaining Machine Learning Operations
- Secure Machine Learning Pipelines
- Maintain Models in Production
Exam Track
At the end of this accelerated course, you’ll sit the following exam at the Firebrand Training centre, covered Certification Guarantee:
Certified Artificial Intelligence Practitioner™ (CAIP) Exam AIP-210
- Duration: 120 Minutes
- Format: Multiple Choice/Multiple Response
- Number of questions: 80
- Passing score: 60%
What's Included
Your accelerated course includes:
- Accommodation *
- Meals, unlimited snacks, beverages, tea and coffee *
- On-site exams **
- Exam vouchers **
- Practice tests **
- Certification Guarantee ***
- Courseware
- Up-to 12 hours of instructor-led training each day
- 24-hour lab access
- Digital courseware **
- * For residential training only. Accommodation is included from the night before the course starts. This doesn't apply for online courses.
- ** Some exceptions apply. Please refer to the Exam Track or speak with our experts
- *** Pass first time or train again free as many times as it takes, unlimited for 1 year. Just pay for accommodation, exams, and incidental costs.
Prerequisites
Before attending this accelerated course, you should have:
- Several years of experience with computing technology, including some aptitude in computer programming.
OR
- Be familiar with the concepts that are foundational to data science, including:
- The overall data science and machine learning process from end to end: formulating the problem; collecting and preparing data; analysing data; engineering and pre-processing data; training, tuning, and evaluating a model; and finalizing a model.
- Statistical concepts such as sampling, hypothesis testing, probability distribution, randomness, etc.
- Summary statistics such as mean, median, mode, interquartile range (IQR), standard deviation, skewness, etc.
- Graphs, plots, charts, and other methods of visual data analysis.
- Be comfortable writing code in the Python programming language, including the use of fundamental Python data science libraries like NumPy and pandas.
Unsure whether you meet the prerequisites? Don’t worry. Your training consultant will discuss your background with you to understand if this course is right for you.
Reviews
Here's the Firebrand Training review section. Since 2001 we've trained exactly 134561 students and asked them all to review our Accelerated Learning. Currently, 96.41% have said Firebrand exceeded their expectations.
Read reviews from recent accelerated courses below or visit Firebrand Stories for written and video interviews from our alumni.
"It's a third course I have with this instructor. His classes are fast-paced and well structured."
Anonymous. (8/1/2024 (Monday) to 10/1/2024 (Wednesday))
"A super engaging and pleasant lecturer."
Michael White, Lloyds Banking Group. (10/7/2023 (Monday) to 12/7/2023 (Wednesday))
"Facility is excellent. Training delivery and interaction with the trainer also excellent and the material is straightforward to follow with a good mix of theory and practical."
Mark Jeffery, Lloyds Banking Group. (10/7/2023 (Monday) to 12/7/2023 (Wednesday))
"Our trainer kept the course very interesting and now I feel equipped with even more knowledge which I can bring to the working world."
Anonymous (3/7/2023 (Monday) to 5/7/2023 (Wednesday))
"A very useful and informative event that will help my career."
Anonymous (3/7/2023 (Monday) to 5/7/2023 (Wednesday))