What Our Learners Say
This is my second time to attend a training by Casugol and both times I was able to get something from it which can be applied to my current occupation. Dwayne is very patient and attends to your question, which is a good quality of how a trainer should be. Also, even at the last minute request, he extended to give way to our company's townhall.. you ought to try them! Awesome to Learn, Thanks Sir Dwayne. Good beginner class to learn the foundation of the Data Analytics! Friendly trainer. Always stopping to ask if we have any questions and asking us questions to make the lesson interactive. Superb training experience! Very in depth seminar conducted by Mr Dwayne Ong on CDTP course. We appreciate your time and support for the past 2 days on the course. Mr Dwayne was very knowledgeable and offered very valuable information. Great tools to apply for organizations moving towards Digitalizations Bahagian Pengambilan Pelajar IPT
Very informative class. Participants able to learn latest trend in digital trend It was an amazing experience. A very interesting learning experience outside my expertise Nice experience on this training. Thank you. Machine learning is very interesting Learn enjoy with CASUGOL😁 
Upcoming Batches
| Schedule |
Time (SGT / UTC +8) |
Sessions |
Date |
| Full-Time |
9:30am to 5:30pm
(Daily) |
5-Sessions |
8 to 12 Nov | 10 to 14 Jan | 14 to 18 Mar |
| Register Here
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Course Information
- Duration: 5 Day / 40 Hours
- Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
- Who Should Attend: Data Analyst, Finance Analyst, HR Analyst, System Analyst, CIO, or Anyone who are interested in pursuing a career in the areas of Artificial Intelligence
Course Objective
Acquire advanced knowledge and technical competency Natural Language Processing (NLP) and Deep Learning.
Learn the key components in Natural Language Processing (NLP), semantic analysis, and featured engineering with Python Programming.
Pre-Requisite
It is preferred that participants successfully completed and pass Certified Machine Learning Expert (CMLE) or Python Programming Essentials (PPE)
Examination
Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Natural Language Processing (NLP) and Python Programming based on the syllabus covered
Module 1
Introduction to Natural Language Processing (NLP)
Topics Covered
- What is Natural Language Processing (NLP)
- Applications of Natural Language Processing (NLP)
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- Using Natural Language Processing with Python
- Understanding and setting up Python NLTK package
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Module 2
Understanding Data For Natural Language Processing (NLP)
Topics Covered
- Introduction to Corpus and Corpora
- Categorical and Qualitative Data Attributes
- Numerical and Quantitative Data Attributes
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- File Formats for Corpora
- Dataset Preparation for NLP Application
- Web scraping
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Module 3
Introduction to Morphological Analysis
Topics Covered
- Understanding Morphology
- Morphemes and Stem
- Using Morphological Analysis to Identify a Word
- Classification of Morphemes
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- Lexical Analysis
- Tokens and Part of Speech tags
- Stemming vs Lemmatization
- Performing Syntactic Analytics
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Module 4
Performing Semantic Analysis
Topics Covered
- Semantic Analysis
- Understanding Lexical Semantics
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- Hyponymy and hyponyms
- Application of Semantic Analysis
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Module 5
Ambiguity in Natural Language Processing (NLP)
Topics Covered
- What is Ambiguity
- Lexical Ambiguity
- Syntactic Ambiguity
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- Semantic Ambiguity
- Pragmatic Ambiguity
- Performing Pragmatic Analysis
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Module 6
Pre-Processing in Natural Language Processing
Topics Covered
- Handling Corpus-Raw Text
- Handling of Corpus-Raw Sentences
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- Preprocessing Essentials
- Customized Preprocessing
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Module 7
Featured Engineering and NLP Algorithms
Topics Covered
- What is feature engineering?
- Parsers and Parsing in Natural Language Processing (NLP)
- POS Tagging and POS Taggers
- Name Entity Recognition
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- Introduction to n-grams
- Bag of Words
- Statistics for NLP
- Probabilistic Theory for NLP
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Module 8
Key Components of Featured Engineering
Topics Covered
- What is TF-IDF
- Using of textblob
- Python Scikit-learn
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- Vectorization, Normalization
- Probabilistic Models
- Indexes
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Module 9
Advanced Featured Engineering Techniques
Topics Covered
- Understanding Recall Word Embedding
- Distributional Semantics with word2vec
- Unsupervised Distribution Semantic Mode
- Blackbox to Whitebox
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- Core Components of word2vec Model
- Logic of word2vec Model
- Neural Network Algorithm
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Natural Language Processing Developer (NLPD) involves rigorous usage of real-time case studies, hands-on exercises and group discussion
What Past Participants Say
The examples and cases shared in class are delivered in a clear, structured and easy to understand manner. It provide me with confidence to kickstart my own Machine Learning project.
Falhuddin Bin Nurdin
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This course provide me with the detailed information required and essential tips how to explore more into the subject. The trainer is very helpful throughout the course. With his encouragement, I can understand the topics with ease even when I am not experience in programming.
Shalini Karthik
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Why CASUGOL
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Customization of Programs for specific industry, organisation, government agencies, statutory boards.
Flexible programmes designed to cater to the individual needs of participants, whether for professional upskilling, or for general interest.
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Benefit from contribution from leading Industry Experts, Academics, and Researchers from across the world.
Opportunities for employers to develop their workforce and for individuals to enhance their career.
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Dynamic learning environment that providing participants with professional networking opportunity.
Online support for participants after the training. |
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