AED 8,000
This course includes
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Course Type: Advanced
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Course Partner: 
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Duration:110 Hours of Learning
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Medium:Self-Paced
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Overview
This course focuses on software development, applied math and statistics, and business analysis skills so as to apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.
You will learn how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions ensuring that they protect the privacy of users.
Pre-requisites
- Complete the CertNexus AIBIZ™ (Exam AIZ-110) course (or) Have a high-level understanding of fundamental AI concepts, including, but not limited to machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing.
- Have experience working with databases and a high-level programming language such as Python, Java, or C/C++.
- The student may have one of the required skills such as:
A programmer looking to develop additional skills to apply machine learning algorithms to business problems (or) A data analyst, with strong understanding of applied math and statistics to solve business problems, looking to develop technology skills related to machine learning.
Take-away skills
- Specify a general approach to solve a given business problem that uses applied AI and ML.
- Collect and refine a dataset to prepare it for training and testing. • Train and tune a machine learning model.
- Finalize a machine learning model and present the results to the appropriate audience.
- Build linear regression models.
- Build classification models.
- Build clustering models.
- Build decision trees and random forests.
- Build support-vector machines (SVMs).
- Build artificial neural networks (ANNs).
- Promote data privacy and ethical practices within AI and ML projects.
Certification
KHDA approved course completion certificate
The course is a step towards CertNexus® Certified Artificial Intelligence (AI) Practitioner Exam AIP-110 (CAIP) certification. The exam will test the following domains:
- Applied Artificial Intelligence and Machine Learning in business
- Problem formulation
- Data collection, comprehension, cleaning, and engineering
- Algorithm selection and model training
- Model handoff
- Ethics and oversight
Companies using Artificial Intelligence (AI)
AED 8,000
This course includes
-
Course Type: Advanced
-
Course Partner:
-
Duration:110 Hours of Learning
-
Medium:Self-Paced
Share this course
Why Learn CAIP?
The Certified Artificial Intelligence Practitioner™ (CAIP) training program is designed for data science practitioners seeking vendor-neutral, cross-industry foundational knowledge of AI and Machine Learning (ML) concepts, technologies, algorithms, and applications for use in a wide variety of AI-related job functions.
Curriculum
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1
Solving business problems using AI and ML
- Identify AI and ML solutions for business problems
- Formulate a machine learning problem
- Select appropriate tools
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2
Collecting and refining the dataset
- Collect the dataset
- Analyze the dataset to gain insights
- Use visualizations to analyze data
- Prepare data
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3
Setting up and training a model
- Set up a machine learning model
- Train the model
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4
Finalizing a model
- Translate results into business actions
- Incorporate a model into a long-term business solution
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5
Building linear regression models
- Build a regression model using linear algebra
- Build a regularized regression model using linear algebra
- Build an iterative linear regression model
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6
Building classification models
- Train binary classification models
- Train multi-class classification models
- Evaluate classification models
- Tune classification models
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7
Building clustering models
- Build k-means clustering models
- Build hierarchical clustering models
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8
Building advanced models
- Build decision tree models
- Build random forest models
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9
Building support-vector machines
- Build SVM models for classification
- Build SVM models for regression
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10
Building artificial neural networks
- Build multi-layer perceptrons (MLP)
- Build convolutional neural networks (CNN)
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11
Promoting data privacy and ethical practices
- Protect data privacy
- Promote ethical practices
- Establish data privacy and ethics policies
Our Partner
CertNexus is a vendor-neutral certification body, providing emerging technology certifications and micro-credentials for business, data, developer, IT, and security professionals. CertNexus’ mission is to assist closing the emerging tech global skills gap while providing individuals with a path towards rewarding careers in Cybersecurity, Data Science, Internet of Things, and Artificial Intelligence (AI)/Machine Learning. Successful CertNexus certification candidates come from representative organizations such as Ahold Delhaize, Barclays, Canon, Cisco, Ingram, Intel, Kaspersky, Optum, Starbucks, U.S. Air Force, U.S. Army, Verizon, Xerox, Zappos, and universities spanning over fifty countries.
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4.6
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FAQs
Yes, the course is self-paced course to be completed over 6 months. It can be done while studying for a degree program or alongside a full-time job.
No, this program is a stand-alone certification program.
Yes, the course offers a KHDA approved completion certificate.
Upon completion learners will be prepared to take the CAIP (AIP) exam offered on Pearson VUE by CertNexus.
Within 48 hours of enrolling for the course.
Yes, you can pay in two installments. The first installment will be made prior the commencement of the course and the second installment will be automatically debited on the card on file at an agreed date.
Fee Payment Policy
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