Build your knowledge of Artificial Intelligence
from the ground up and be on your way to be a competent practitioner
The Artificial Intelligence Foundation provided by IABAC caters to those individuals who are making a new entry into the field of AI. The course consists of the basics of Artificial Intelligence and Machine Learning, basics of Deep Learning.
Duration
3 days / 24 hours
Level
Beginner to Intermediate
Delivery
100% Online - Instructor Led
Request For Information
Key Features
- 24 hours of instructor led training
- Fully Online
- Class recording available
- Interactive Learning
- Additional Coaching Session
- 100% HRDF SBL-KHAS Claimable!
Pre-Requisites
- No mandatory prerequisites
- 2. Recommended essential knowledge in:
a. Mathematics: Calculus, Statistics, Linear Algebra, Probability
b. Machine Learning and Python/R Programming - Training: Though formal training is not mandatory; it is recommended to attend IABAC® registered course through Registered Education Partners
Who Should Join
- Individuals pursuing a career in Artificial Intelligence
- Beginners and students with good Machine Learning knowledge aspiring a career in Artificial Intelligence
Key Learning Outcomes
Upon completion, participants should be able to demonstrate each of the following outcome:-
- Understand how Python is used for artificial intelligence and deep learning
- Gain knowledge on Tensorflow 2.0 and Keras to apply in artificial intelligence projects
- Develop a solid understanding of deep learning
- Understand and apply core concepts of machine learning in artificial intelligence projects
IABAC Exam Information
Materials Permitted
- The examination is ‘closed book’
- No material permitted and No Internet Access
Exam duration & format
- The computer-based exam is timed for 60 mins. No breaks allowed.
- The exam consists of 25 Multiple-Choice Questions with three difficulty levels: easy, medium and difficult questions
- Each question carries 5 Marks / 10 Marks
- No Negative marking
Exam mode
- IABAC® certification exam is computer based and conducted through IABAC® Exam portal only
- Candidates require a computer with internet and webcam (video and audio) to take the exam
- Computer screen recording permission should be granted
Pass criteria
- The candidate needs to score 60% or higher in order to pass the examination
- The results will be declared after validation of the exam recording video session and identity proof verification.
Results timeline
- The preliminary results are usually released within 9 days of the exam date
- The official results are usually released within 15 days from the exam date
Certificate Issuance
- IABAC® e-certificate will be issued through the candidate’s registered email
- The e-certificate is digital verifiable at https://www.iabac.org/verify-certificate
- The candidate has license to share digital certificate validation in professional networking portals such as www.linkedin.com
- The candidate has a license to print physical copy (hardcopy) of the certificate
Course Modules Covered in the Artificial Intelligence Foundation program
Module 1 - Introduction to Artificial Intelligence
Introduction to Artificial Intelligence
- History of Artificial Intelligence (AI)
- Five domains of AI
- Why AI now?
- Limitation of AI
Module 2 - Machine Learning Primer
Machine Learning Primer
- Machine Learning Primer
- Machine Learning core concepts, scalable algorithms, project workflow.
- Objective Functions and Regularization
- Understanding Objective Function of ML Algorithms
- Metrics, Evaluation Methods and Optimizers
- Popular Metrics in Detail: R2 Score, RMSE, Cross Entropy, Precision, Recall, F1 Score, ROC-AUC, SGD, ADAM
- Artificial Neural Network
- ANN in detail, Forward Pass and Back Propagation
- Machine Learning Vs Deep Learning
- Core difference b/w ML and DL from implementation perspective
Module 3 - Advanced Python For Deep Learning
Advanced Python For Deep Learning
- Python Programming Primer
- Installing Python, Programming Basics, Native Data types
- Class, Inheritance and Magic Functions
- Python Classes, Inheritance Concepts, Magic Functions
- Special Functions in Python
- Overview, Array, selecting data, Slicing, Iterating, Array Manipulations, Stacking, Splitting arrays, Key functions
- Decorators and Special Functions
- Decorators implementation with class
- Context Manager ‘with’ in Python
- Context Manager Application
- Exception Handling
- Try and Catch block
- Python Package Management
- Bundling and export python packages
Module 4 - Tensorflow 2.0 And Keras For Deep Learning
Tensorflow 2.0 And Keras For Deep Learning
- TensorFlow 2.0 Basics
- TensorFlow core concepts, Tensors, core APIs
- Concrete Functions, Datatypes, Control Statements
- Polymorphic Functions, Concrete Functions, Datatypes, Control Statements, NumPy, Pandas
- Autograph eager execution
- tf.function autograph implementation
- Keras (TensorFlow 2.0 Built-in API) Overview
- Sequential Models, configuring layers, loading data, train and test, complex models, call backs, save and restore Neural Network weights
- Building Neural Networks in Keras
- Building Neural networks from scratch in Keras
Module 5 - Mathematics for Deep Learning
Mathematics for Deep Learning
- Linear Algebra
- Vectors, Matrices, Linear Transformation, Eigen Vectors, Matrix Operations, Special Matrices
- Calculus – Derivatives: Calculus essentials, Derivatives and Partial Derivatives, Chain Rule, Derivativesof special functions
- Probability Essentials: Probability basics and notations, Conditional probability, Essential Probability theorems for Machine Learning
- Special functions: Relu, Sigmoid, SoftMax, Popular Loss Functions – Cross Entropy, Quadratic Loss Functions
Module 6 - Deep Learning Foundation
Deep Learning Foundation
- Deep Learning Network Concepts
- Core concepts of Deep Learning Networks
- Deep Dive into Activation Functions
- Building simple Deep Learning Network
- Tuning Deep Learning Network
Our Training Methodology
Practical Assignments
We provide hands-on assignments that requires practical implementation.
Virtual Coaching Sessions
Online coaching sessions that happen over the phone, via video, or on a web platform.
1 Year Access to LMS
Get access to learning resources upto 1 year of class completion.
Live Project Experience
Hands-on learning and training gives participants the opportunity to experience real world situations.
Online Assessments
Participants can assess reflect on their own learning and their level/skills.
Free Industry Webinars
Stay current on market research trends, learn best practices through our webinar sessions.
Program Key Highlights
48 hours of Remote Online Learning
Additional Coaching Hours
Live Hands-on Projects
Certified by International Body
Mentorship with Industry Experts
Designed for Beginners & Professionals
Request For Information
Program Benefits
International Credential
IABAC® is a widely recognized credentialing framework based on European commission funded EDISON Data Science body of knowledge. This credential provides distinction as high potential certified Data Science Professionals enabling better career prospects.
Global Opportunities
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
Specialization
IABAC Certification designed to cater to the job requirements of all experience levels and specializations, which suits roles aligned with the industry standards.
Relevant and updated
IABAC® CPD (Continuing Professional Development) program enables credential holders to update their skills and stay relevant to the industry requirements.
Higher Salaries
On an average, a certified professional earns 30-40% more than their non-certified as per recent study by Forbes.
Summits & Webinars
In addition, IABAC members will have exclusive access to seminars and Data Science summits organised by IABAC partners across the globe.
Get Professionally Certified
Upon successfully completing this program, participants will be awarded the Artificial Intelligence Foundation Certification by International Association of Business Analytics Certification (IABAC).
This award is a validation to the efforts taken to master the domain expertise that will set you apart from your competition.
Be a part of the global network of data science professionals and join the community across sectors.
Get in Touch With Us Today!
This training program is suitable for anyone who intends to enter into the field of Artificial Intelligence. This program is being conducted in Malaysia and can be joined by anyone, anywhere in the world remotely.
Program Fee
Funding price MYR 3700 per pax .
Funding Schemes for Companies who are claiming from their HRDF levy or from the MDEC MyWiT scheme.
Limited scholarships available for early self applying individual applicants.
Find out how you can qualify for a scholarship.
Enquire NOW on the various funding options available.
Limited scholarships available for early self applying individual applicants.
Find out how you can qualify for a scholarship.
Enquire NOW on the various funding options available.
One-time fee. One year access to course materials and resources.
Thulija Academy is a HRDF registered training provider. Our panel of expert trainers provide technology training for some of the biggest organizations in Asia.
READY TO KICKSTART YOUR CAREER?
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