• Home
  • Solving Problems with Machine Learning

Solving Problems with Machine Learning

Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Beginner
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Suite Pejabat Korporat, KL Gateway, No 2, Jalan kerinchi, Gerbang kernichi Lestari, 59200 Kuala Lumpur, Malaysia
Penang: Jalan Sungai Dua, 11700 Penang, Malaysia.

Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.

Solving Problems with Machine Learning

Course Code: C425
  • HRDF

Be the first to review this product

What's This Course About

Embark on a transformative learning journey with our "Solving Problems with Machine Learning" course. Tailored for professionals eager to master AI, this course equips you with the ability to apply machine learning techniques to solve complex challenges in your industry. You'll uncover the secrets of data-driven decision-making and predictive analytics, ensuring you're able to identify patterns, make informed predictions, and craft innovative solutions. Each session is designed to build your proficiency in harnessing the power of AI, preparing you to take on problems with confidence and creativity.

This course is not just about learning the theory; it's a springboard into the world of artificial intelligence applications. Through a blend of expert instruction and hands-on practice, you'll learn to navigate the machine learning landscape, develop AI strategies, and implement solutions that drive results. Whether you're tackling issues in finance, healthcare, or e-commerce, our training will provide you with the knowledge and tools to make an impact. Get started on Shopee and other platforms in just one day and join the ranks of skilled professionals who are making strides with the power of machine learning.

WSQ Funding

Full Fee 1,050.00 Before GST
GST 94.50 9% of fee
Baseline Nett 619.50 SG/PR age 21+ · 50% funded
MCES / SME Nett 409.50 SG age 40+ · 70% funded
Funding and Grant Applications

No funding is available for this course.

Course Fee

MYR1,050.00

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Disclaimer: The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

  • We may provide consultation related to the subject matter after the course.
  • Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

Topic 1 - Introduction to Machine Learning

What is Machine Learning

Machine Learning in Real life

Types of Machine Learning

Key ML Models

Installing Weka

Load Dataset to Weka

Build Your First Classifier

Topic 2 - Classification

What is Classification?

K-Nearest Neighbours (KNN)

Support Vector Machine (SVM)

Naive Bayes

Decision Tree (DT)

Topic 3 - Regression

What is Regression?

Linear Regression

Support Vector Regression

K-Nearest Neighbour Regression

Topic 4 - Ensemble Methods

What is Ensemble Methods?

Bagging

Random Forest

Stacking

Topic 5 - Clustering

What is Clustering?

K-Means Clustering

Hierarchical Clustering

Topic 6 - Neural Network

What is Neural Network?

Multilayer Perceptron Classifier

Topic 7 - Problem Solving through Machine Learning

Problem Definition

Data Conceptualization

Data Gathering

Feature Engineering

Algorithm Spot Check

Fine Tuning Model

Pitfalls

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

Job Roles

Job Roles

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Research Scientist
  • Business Intelligence Specialist
  • Data Engineer
  • Software Developer (interested in ML)
  • Statistician
  • Predictive Modeler
  • AI Solutions Architect
  • Quantitative Researcher
  • Data Visualization Specialist
  • Analytics Consultant
  • Product Manager (focused on AI/ML products)
  • Innovation Specialist

Trainers

Trainers

Saeid is co-founder of Skymics Sdn Bhd. He has 8 years of experience in the field of IoT (Internet of Things) and Information Technology. He is a certified IBM IoT Practitioner and instructor, and a Certified Citizen Data Scientist Train-The-Trainer. He has been co-inventor of 3 inventions during the last 4 years.

Review

Write Your Own Review

You're reviewing: Solving Problems with Machine Learning