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HRD Corp Approved Training Provider Malaysia - Industrial 4.0 Certification Training and Education

Predictive Analytics with Orange

Discover the realm of predictive analytics with our Predictive Analytics with Orange training at Tertiary Courses. Orange, renowned for its user-friendly interface and comprehensive modules, has emerged as a leading tool in the analytics community. This course ensures participants unravel the extensive capabilities of Orange, enabling them to anticipate trends, patterns, and behaviors from their data.

Begin with a comprehensive overview of Orange and its landscape. Trainees will delve deep into classification, predictive modeling, and regression analysis techniques that power data-driven decisions. Progressing further, participants will explore advanced modules like clustering and image analytics, ultimately culminating in the powerful realm of dimension reduction. Join us and supercharge your predictive analytics skills, turning data insights into actionable strategies.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant

HRD Corp Claimable Course for Employers Registered with HRD Corp

HRDF claimable

Course Code: M547

Course Booking

MYR1,000.00

Course Date

Course Time

* Required Fields

Post-Course Support

We provide free 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 asap.

Course 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.
Note the minimal class size to start a class is 3 Pax.


Course Details

Topic 1 Overview of Predictive Analytics and Orange

  • Data Mining Process
  • Introduction to Machine Learning
  • Supervised vs UnSupervised Learnings
  • Overview of Orange

Topic 2: Data Preparation

  • Load Data to Orange
  • Interactive Visualization
  • Filter Data
  • Merge and Concat Data
  • Preprocess Data
  • Feature Statistics
  • Save Data

Topic 3: Regression

  • What is Regression
  • Linear Regression
  • Model Evaluation Metrics for Regression
  • Regularization

Topic 4: Classification

  • What is Classification
  • Classification Algorithms
  • K-Fold Cross Validation
  • Model Evaluation Metrics for Classification
  • Confusion Matrix
  • ROC Analysis for Binary Classification

Topic 5: Clustering

  • What is Clustering
  • K-Means Clustering
  • Silhouette Analysis
  • Hierarchical Clustering

Topic 6: Dimension Reduction

  • What is Dimension Reduction
  • Principal Component Analysis (PCA)
  • Feature Ranking
  • t-SNE and MDS

Topic 7: Association Analysis

  • What is Association Analysis
  • Apriori Algorithm
  • Association Analysis with Orange

Course Info

Prerequisite:

This is beginner course. No prori programming language is required

Software Requirement:

  • Download and Install Orange before the class

HRDF Funding

Please refer to this video https://youtu.be/Kzpd-V1F9Xs

1-     HRD Corp Grant Helper

How to submit grant applications for HRD Corp Claimable Courses

2-     Employers are required to apply for the grant at least one week before training commences.

Employers must submit their applications with supporting documents, including invoices/quotations, trainer profiles, training schedule and course content.

3-     First, Login to Employer’s e-TRIS account -https://etris.hrdcorp.gov.my

Second, Click Application

4-     Click Grant on the left side under Applications

5-     Click Apply Grant on the left side under Applications

6-     Click Apply

7-     Choose a Scheme Code and select HRD Corp Claimable Courses: Skim Bantuan Latihan Khas. Then, click Apply

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Select a relevant focus area. For Employer-Specific Courses, select ‘Not Applicable’.

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Insert MiCAS Application number

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29-  Once the New Grant Application is successfully submitted, the Grant Officer will evaluate the application accordingly. The application may be queried if additional information is required.

The application status will be updated via the employer’s dashboard, email, and the e-TRiS inbox.

Job Roles

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • Research Scientist
  • Quantitative Researcher
  • Bioinformatics Scientist
  • Data Mining Specialist
  • Customer Insights Analyst
  • Marketing Analytics Specialist
  • Predictive Analytics Specialist
  • Healthcare Data Analyst
  • Financial Modeler
  • E-commerce Data Specialist
  • User Behavior Analyst

Trainers

Dr. Aanand: Dr. Aanand is a Full Stack Data Scientist who once had a torrid love affair with Physics. He has consulted and published in the area of Public Health, Electricity Markets, Telecom, BFSI, Advertising & Communication Strategies and Digital & Social Media Technologies. He has worked on assignments with international agencies such as International Monetary Fund, World Bank, Royal Netherland Embassy etc. besides MNCs like Tata Consultancy Services, Kie Square Consulting and several government organizations of national importance. He regularly conducts general training programs in Python (Pandas, NumPy, SciPy, Matplotlib, Bokeh), R (dplyr, rstanarm, knitR, ggplot2), Data Visualization (Tableau, D3.js) and Machine Learning (Reinforced Learning, Scikit Learn) and specialized training programs on Structural Equation Modeling and SAP Hana. He holds a doctorate in Operations Research from Indian Institute of Management Ahmedabad and a post-graduate in Physics from the University of Mumbai. He has advanced training in mathematical programming including optimization, advanced multivariate data analysis, and simulation techniques. When he is not teaching or consulting he can be found meditating or heading for an adventurous trek.

Customer Reviews (5)

will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Required a few days training to fully understand the overall course (Posted on 18/04/2024)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 21/03/2022)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
The course content is quite comprehensive to be covered in just 1 day. For one to practice it with Orange it will be best to run for at least for 3 days.
Trainer knowledge is good but time is too short to catch up everything in just 1 day (Posted on 30/07/2021)
might recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 28/07/2021)
will recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
This course should be done in three days because the content is a lot.
The instructor is very knowledgeable. (Posted on 27/07/2021)

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