Artificial intelligence and machine learning are essential components of the “toolsets” of organizations in both the public and private sectors today. Use of these technology solutions is expected to continue to rapidly expand to solve a wide variety of business and mission challenges.
When used effectively and responsibly, AI and machine learning solutions provide actionable insights to help drive critical decisions and enable organizations to create exciting, new and innovative products and services.
This self-paced, online course was developed by FedLearn content partner, CertNexus, to prepare for, and take, the Certified AI Practitioner certification exam. You will learn how to apply various approaches and algorithms to solve business and mission problems through AI and machine learning—all while following a methodical workflow for developing data-driven solutions.
The CertNexus CAIP is an in-demand, fast-growing certification program to equip you with vendor-neutral, cross-industry knowledge of AI and machine learning concepts and skills. After completing the program, you will be able to select, train and implement AI and machine learning solutions.
After registering for the course, you will receive the CAIP exam prep eBook that will guide you through the course materials and lab activities, and access to the online lab and certification exam vouchers.
What You Will Learn
- Solve a given organizational problem using AI and machine learning
- 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
- 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
It is recommended that you space the training over the course of at least six weeks (one lesson per week) to allow ample time to absorb the content and prepare to sit for the CertNexus CAIP exam. Note that this is only a suggestion—you are free to complete the reading assignments and activities at your own pace.
Course Content
Lesson 1: Solving Business Problems Using AI and Machine Learning
- Identify AI and machine learning solutions for business problems
- Formulate a machine learning problem
- Select approaches to machine learning
Lesson 2: Preparing Data
- Collect data
- Transform data
- Engineer features
- Work with unstructured data
Lesson 3: Training, Evaluating and Tuning a Machine Learning Model
- Train a machine learning model
- Evaluate and tune a machine learning model
Lesson 4: Building Linear Regression Models
- Build regression models using linear algebra
- Build regularized linear regression models
- Build iterative liner regression models
Lesson 5: Building Forecasting Models
- Build univariate time series models
- Build multivariate time series models
Lesson 6: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
- Train binary classification models using logistics regression
- Train binary classification models using k-nearest neighbor
- Train multi-class classification models
- Evaluate multi-class classification models
- Tune classification models
For more information regarding the domains and objectives covered by the CertNexus CAIP exam, download the exam blueprint here.
Who Should Take This Course
This online course is perfect for professionals—for instance, data science practitioners, software developers or analysts—interested in enhancing their knowledge of the data science process specific to AI systems, particularly machine learning models, to solve business or mission problems. It was designed for professionals who wish to take the CAIP exam.
It is highly recommended that learners possess several years of experience in computing technology, including programming. In addition, to ensure your success in this course and the exam, you should be familiar with foundational data science concepts including:
- Overall data science and machine learning processes from end to end
- Statistical concepts, such as sampling, hypothesis testing, probability distribution and randomness
- Summary statistic, including mean, median, mode, interquartile range, standard deviation and skewness
- Graphs, plots, charts and other methods of visual data analysis
Prerequisites
It is highly recommended that you take the FedLearn courses, Introduction to AI/Machine Learning Concepts & Terminology (AIData109) and Introduction to Responsible AI in the DoD (AIETHICS101), prior to enrolling in CAIP101.
Course Certificate
A certificate of completion can be downloaded after successfully finishing the course (following the FedLearn honor code).
Course Format
Reading assignments based on the CertNexus CAIP exam prep eBook and participation in online lab activities
Course Pricing
A bundled package of the course eBook, online lab voucher and CDSP exam voucher is available for purchase for $693.
After purchasing, the eBook, vouchers and information on accessing the lab and exam will be emailed to you. You will be able to access the lab for six (6) months after acquiring the voucher.
If you are interested in learning about special team rates for Federal government and government contractor organizations, email [email protected].
Continuing Education Units
This course provides 30 CEUs.
