Certified Machine

Learning Expert

Become a certified machine learning expert
and take your career to the next level.


5 Days / 40 Hours / 6 Modules
+ 3 month coaching + 1 year eLearning access


Get in Touch With Us
Certified Machine

Learning Expert

Become a certified machine
learning expert and take your
career to the next level.

5 Days / 40 Hours / 6 Modules
+ 3 month coaching + 1 year eLearning access

Become a certified machine learning expert and take your career to the next level.

The Certified Machine Learning Expert course provided by IABAC is globally recognised , and helps in providing value addition, for starting a career in Machine Learning. It consists of an introduction to Machine Learning and the various ML algorithms, Advanced Techniques in Machine Learning.
Key Learning Outcomes

Upon completion, participants should be able to demonstrate each of the following outcome:-

  • Master Machine Learning on Python
  • Know which Machine Learning model to choose for each type of problem
  • Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, etc.
  • Make robust Machine Learning models
IABAC Exam Information
Course Modules Covered in the Machine Learning Expert Certification program
Module 1 - Python For Data Science

Python For Data Science

  1. Introduction to Data Science with Python
  2. Python Basics: Basic Syntax, Data Structures
  3. Data objects, Math, Comparison Operators, Condition Statements, loops, lists, tuples, dicts, functions
  4. Numpy Package
  5. Pandas Package
  6. Python Advanced: Data Munging with Pandas
  7. Python Advanced: Visualization with Matplotlib
  8. Exploratory Data Analysis: Data Cleaning, Data Wrangling
  9. Exploratory Data Analysis: Case Study
Module 2 - Statistics for Data Science

Statistics for Data Science

  1. Introduction to Statistics
  2. Harnessing Data
  3. Exploratory Analysis
  4. Distributions
  5. Hypothesis & Computational Techniques
  6. Correlation & Regression
Module 3 - SQL For Data Science

SQL For Data Science

  1. Install SQL packages and Connecting to DB
  2. RDBMS (Relational Database Management) Basics
  3. Basics of SQL DB, Primary Key, Foreign Key
  4. SELECT SQL command, WHERE Condition
  5. Retrieving data with SELECT SQL command and WHERE Condition to Pandas DataFrame.
  6. SQL JOINs
  7. Left Join, Right Joins, multiple joins
Module 4 - Machine Learning Associate

Machine Learning Associate

  1. Machine Learning Introduction
  2. What is ML? ML vs AI. ML Workflow, Statistical Modelling of ML. Application of ML
  3. Machine Learning Algorithms
  4. Popular ML Algorithms, Clustering, Classification and Regression, Supervised vs Unsupervised
  5. Choice of ML
  6. Supervised Learning
  7. Simple and Multiple Linear regression, KNN, and more
  8. Linear Regression and Logistic Regression
  9. Theory of Linear Regression, hands on with use cases
  10. K-Nearest Neighbour (KNN)
  11. Decision Tree
  12. Naïve Bayes Classifier
  13. Unsupervised Learning: K-Means Clustering
Module 5 - Machine Learning Expert

Machine Learning Expert

  1. Advanced Machine Learning Concepts
  2. Tuning with Hyper parameters
  3. Random Forest – Ensemble
  4. Ensemble theory, Random Forest Tuning
  5. Support Vector Machine (SVM)
  6. Simple and Multiple Linear Regression, KNN
  7. Natural Language Processing (NLP)
  8. Text Processing with Vectorization, Sentiment Analysis with Text Blob, Twitter Sentiment Analysis.
  9. Naïve Bayes Classifier
  10. Naïve Bayes for Text Classification, News Articles tagging
  11. Artificial Neural Network (ANN)
  12. Basic ANN for Regression and Classification
  13. TensorFlow Overview
  14. Deep Learning Intro
Module 6 - Model Deployment

Model Deployment

  1. Basics of Application Program Interface (API)
  2. API basics, Loosely Coupled Architecture
  3. Installing Flask
  4. Installation and configuring Flask and cross domain authentication
  5. End to End ML project with API deployment
  6. Complete project flow with API deployment and assessing through the website
  7. Various Deep Learning models in practice and applications
  8. Convolutional Neural Network CNN Intro
  9. Case Study: Keras–TensorFlow Image Classification
  10. CNN hands on application for Classification Images of Cats and Dogs
Our Training Methodology
Program Key Highlights

online-learning-2
40 hours of Remote Online Learning
learning-hours
Additional Coaching Hours
hands-on
Live Hands-on Projects
certification
Certified by International Body
mentor
Mentorship with Industry Experts
industry
Designed for Beginners & Professionals
Program Benefits


Get Professionally Certified

Upon successfully completing this program, participants will be awarded the Machine Learning Expert 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 Machine Learning. This program is being conducted in Malaysia and can be joined by anyone, anywhere in the world remotely.
Program Fee

MYR 6800 per pax.
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.

One-time fee. One year access to course materials and resources.
 
 



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