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Introduction to the course
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
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.
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 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
Frequently Asked Questions
There are no prerequisites. Our courses are open to students of all backgrounds who are 18 years of age and older. All courses are conducted in English. Video lectures include English subtitles and the option to slow-down, pause, or replay lectures for better retention. Discussion boards are a critical component of each of our courses; therefore, we suggest students have a conversational knowledge of English when pursuing a Certificate of Completion. For any of the art writing courses, students need to be 100% proficient in written English.
You should have an up-to-date web browser such as: Chrome, Safari, Firefox, or Internet Explorer. For more detailed information, please see the guides for supported browsers and basic computer specifications. Our Online Courses can be accessed on a mobile or tablet device, although we strongly encourage you to have access to a desktop or laptop computer and reliable internet connection for certain course components. Former students have told us it is easiest to read discussion threads and complete written assignments on a laptop or desktop computer.
Registration is available on our website. Just follow these simple steps: Click the “Apply Now” button in the top right corner of your screen. Select “Online Courses.” Choose your course(s). You will be asked for basic contact information and your credit card payment. We require full payment at the time of registration and all tuition is billed in US dollars. Be sure to check with your bank or credit card company, as your financial institution may charge a foreign transaction fee.
Our classes are kept small, at no more than 30 students, to better facilitate and encourage personalized interaction with the instructor and fellow participants. Your classmates come from all over the globe and contribute their global perspectives and experience. Some are currently working within the arts while others are just beginning. All classmates share in their passion for the art world.
It is recommended that you begin your course promptly. If you do need to start the course a few days late, contact your instructor as soon as possible after the course has opened to discuss your options. Registration closes on the Friday after the course begins.
Enroll now
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Course customization available
Course customization available
This training course is available to be conducted at your own pace & at your own time. Request for a quotation now and our training advisor will contact you shortly
