DLF395

Deep Learning for Natural Language Processing Training Course

Q: What are the prerequisites for this Deep Learning for NLP course?

This is an advanced-level course requiring undergraduate qualification. You should have a solid foundation in Python programming, basic understanding of machine learning concepts, and familiarity with linear algebra and statistics. Prior experience with neural networks and some exposure to NLP concepts would be beneficial but not mandatory.

Q: What practical skills will I gain from this course?

You'll develop hands-on expertise in text preprocessing techniques (tokenization, stemming, lemmatization), building sentiment analysis models using CNNs, creating sequence-to-sequence models for machine translation, implementing named entity recognition systems, and applying transfer learning with pre-trained models like BERT and GPT-2. All skills are reinforced through practical labs and real-world datasets.

Q: How is the course structured and what teaching methods are used?

This 2-day intensive course combines multiple learning approaches including lectures, slide presentations, hands-on labs, case studies, and group discussions. The course covers 34 structured modules progressing from fundamental deep learning concepts to advanced NLP applications, ensuring both theoretical understanding and practical implementation skills.

Q: What types of real-world applications will I work with?

You'll work with practical applications including sentiment analysis on movie review datasets, machine translation systems, named entity recognition using news articles, and text summarization. The course emphasizes real-world problem-solving using popular datasets and industry-standard techniques.

Q: Will I learn about the latest NLP technologies and models?

Yes, the course covers cutting-edge technologies including modern word embedding techniques (Word2Vec, GloVe, FastText), state-of-the-art pre-trained language models (BERT, GPT-2), and transfer learning approaches. You'll learn how to leverage these advanced models for various NLP tasks while understanding their underlying architectures.

Q: Does the course address ethical considerations in AI development?

Absolutely. The course dedicates significant attention to ethical AI practices, focusing on bias mitigation in NLP models and the developer's responsibility to ensure AI systems benefit society. You'll learn to identify potential biases in language models and implement strategies to create more fair and inclusive AI systems.

Q: Who is this course designed for and what career benefits can I expect?

This course is designed for students and engineers looking to specialize in NLP and deep learning. Upon completion, you'll be equipped with advanced skills highly sought after in roles such as NLP engineer, AI researcher, data scientist specializing in text analytics, and machine learning engineer focusing on language technologies.

Q: Where is the training conducted?

Our online trainings are conducted usually using Zoom or Google Meet. Our physical trainings are normally held in Common Ground, Bangsar South .

Q: Can international participants join this course?

Please check the Available in section to see which countries the course is available in. If your country is not listed, please contact us.

Q: What is the difference between public, corporate, and training provider pricing?

Public pricing : applies for individuals signing up from different companies. Corporate pricing : applies if a company wants to have an intake for its employees only. Training provider pricing : applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.

Master the art of leveraging deep learning within NLP with our comprehensive course designed for aspiring professionals. Embark on a transformative journey through text preprocessing, word embeddings, sentiment analysis, sequence modeling, transfer learning, and more while ensuring ethical AI practices.

Available in:
Malaysia

Face-to-Face Apr 14-15, 2026 9:00 AM - 5:00 PM Tarun Sukhani

Created: April 3rd 2023, 8:30 AM MYT Last Modified: April 3rd 2026, 6:00 AM MYT

advanced

We price match

Public Pricing

MYR 3500

Corporate Pricing

Pax:

Training Fees: MYR 6500/day

Total Fees: MYR 13000 ++

Training Provider Pricing

Pax:

Training Fees: MYR 3200/day

Material Fees: MYR 800

Total Fees: MYR 7200 ++

Features

2 days

16 modules

27 intakes

Full life-time access

English

Technical: 25 pax

Target Audience

students

engineers

Methodologies

lecture

slides

labs

case studies

group discussion

Subsidies

What you'll learn

Develop proficiency in text preprocessing techniques including tokenization, stemming, and lemmatization.
Construct sequence to sequence models for machine translation and summarization.
Explore advanced topics like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for NLP tasks.
Recognize ethical considerations related to AI development in NLP.
Learn about word embeddings and their role in representing semantic relationships between words.
Understand the fundamental concepts of deep learning as they apply to NLP.
Build practical skills by creating sentiment analysis models using CNNs.
Implement transfer learning using state-of-the-art pre-trained language models for various NLP tasks.

Why should you attend?

Deep Learning for NLP is an immersive learning journey that delves into the intricate relationship between neural networks and natural language processing (NLP). This course provides a robust foundation in deep learning concepts, starting with basic neural networks and advancing through to convolutional and recurrent neural networks. Participants will gain hands-on experience in preprocessing text for NLP, mastering techniques such as tokenization, stemming, lemmatization, and stop word removal. The importance of cleaning and normalizing text data is underscored to ensure optimal model performance. The course further explores how numerical vectors are used to represent words through word embeddings, examining semantic similarity and popular embedding techniques like Word2Vec, GloVe, and FastText. Learners will build practical skills in sentiment analysis using deep learning on movie reviews datasets and understand the construction of sequence to sequence models for applications like machine translation. Named entity recognition using news articles datasets solidifies the application of recurrent neural networks. Transfer learning is demystified with hands-on exercises using pre-trained models such as BERT or GPT-2 for tasks including sentiment analysis and named entity recognition. Finally, the course addresses ethical considerations, emphasizing the developer's responsibility to mitigate bias and ensure their models are beneficial to society.

Course Syllabus

Day 1 - Deep Learning Fundamentals

Module 1

Module 2

Short Break

15 mins

Module 3

Module 4

Recap and Q&A

15 mins

Lunch

1 hour

Module 5

Module 6

Short Break

15 mins

Module 7

Module 8

Recap and Q&A

15 mins

End of Day 1

Day 2 - Text Preprocessing Techniques

Module 9

Module 10

Short Break

15 mins

Module 11

Module 12

Recap and Q&A

15 mins

Lunch

1 hour

Module 13

Module 14

Short Break

15 mins

Module 15

Module 16

Recap and Q&A

15 mins

End of Day 2

Ratings and Reviews

( 3 ratings )

100%

( 3 reviews )

Instructor

Tarun Sukhani IT Executive & Data Science Leader

Trainer Profile

TTT Certificate

TTT Accreditation

Tarun Sukhani is a distinguished IT and Finance Executive with over 25 years of comprehensive experience in leading enterprise software solutions, business intelligence, and digital transformation initiatives. As a seasoned professional with a multi-cultural background and international work experience spanning the United States, Malaysia, and beyond, he brings exceptional expertise in designing and delivering highly scalable, concurrent, and performant enterprise systems with budgets reaching $100 million.

With an impressive academic foundation that includes a Doctor of Business Administration (in progress), dual Master's degrees in Information Systems Management and Business Administration from Loyola University Chicago, and multiple Bachelor's degrees from prestigious institutions including the University of Chicago and University of Illinois, Tarun combines theoretical knowledge with practical application. His specialization in Business Intelligence, Data Warehousing, Data Mining, and emerging technologies such as Deep Learning, IoT, and Blockchain positions him at the forefront of technological innovation.

As a polyglot developer with programming experience in over 20 languages and technologies, Tarun demonstrates remarkable versatility across the full software development lifecycle. His technical competencies span from traditional enterprise technologies (.NET, Java, C++) to modern frameworks (Python, Ruby, JavaScript/TypeScript) and cutting-edge platforms including Big Data ecosystems (Hadoop, Spark), Machine Learning frameworks (TensorFlow, DeepLearning4J), and Blockchain technologies (Ethereum, Hyperledger). His expertise extends to cloud architectures, DevOps practices, mobile development, and enterprise application integration.

Currently serving as Project Manager and Scrum Master at TopTal, one of the world's most selective consultancies accepting only 3% of applicants, Tarun provides project oversight and hands-on development for Fortune 500 and FAANG companies. His entrepreneurial spirit is evident through his role as Founder and CTO of Abundent, where he leads digital transformation initiatives and develops innovative solutions in facial recognition, fraud detection, and fintech.

Tarun's extensive training and consulting portfolio includes partnerships with premier training providers across Malaysia, Singapore, Europe, and the United States. He holds numerous industry certifications including Certified Scrum Master, Certified Scrum Professional, ITIL, TOGAF, and specialized certifications in Deep Learning and Information Security. His pedagogical expertise, combined with his technical depth, makes him an exceptional educator capable of translating complex technical concepts into actionable knowledge for diverse audiences across government, academic, and corporate sectors.

21 Students

55 Courses

English, Malay, Spanish

27 Years

( 13 ratings )

100%

( 13 reviews )

Instructor

Mohammed Al-obaydee AI & Data Science Expert

Trainer Profile

TTT Certificate

Dr. Mohammed Al-Obaydee is a distinguished academic and industry professional with extensive expertise in artificial intelligence, machine learning, deep learning, and data science. As an Adjunct Associate Professor at Taylor's University Malaysia and a certified Train the Trainer professional, he brings a unique blend of academic rigor and practical industry experience to his teaching and consulting engagements. With a Ph.D. in Information Science from Universiti Kebangsaan Malaysia (UKM) and over two decades of experience spanning academia and industry, Dr. Al-Obaydee has established himself as a leading authority in advanced computing technologies. His research excellence is evidenced by multiple best paper awards, including recognition at IEEE ACSAT2014 and ITNG 2023 conferences, along with an impressive publication record featuring over 149 citations and an h-index of 6. His research focuses on medical image analysis, computer vision, machine learning applications, and deep learning techniques. As a founder of INNOEYETIVE and AIC4ALL, Dr. Al-Obaydee demonstrates entrepreneurial acumen in leveraging AI and immersive technologies for digital transformation. His industry experience includes successful training and consultation projects with major corporations such as HSBC Bank, OCBC Bank, DELL Malaysia, Amway Malaysia, and EtiQa, where he has delivered specialized programs in data science, analytics, and applied AI engineering. His ability to bridge the gap between theoretical concepts and practical applications makes him an exceptional trainer for professionals seeking to upskill in emerging technologies. Dr. Al-Obaydee's teaching portfolio encompasses a comprehensive range of subjects including Machine Learning, Deep Learning, Data Analytics, Data Engineering, Parallel Computing, and Advanced Data Structures. He has supervised numerous master's students and research projects at both Taylor's University and the International Islamic University Malaysia (IIUM), focusing on cutting-edge topics such as deep reinforcement learning, medical image classification, fraud detection, and natural language processing. His international speaking engagements and extensive training experience across multiple organizations demonstrate his exceptional communication skills and ability to make complex technical concepts accessible to diverse audiences.

114 Courses

English

21 Years

( 0 ratings )

( 0 reviews )

Course Reviews

"A great course for anyone looking to dive deeper into NLP. Overall pretty well structured. But, a little bit difficult if you are not brushed upon the basics beforehand. "

"Very clearly articulated. A lot of concepts explained, really accurate and hit the mark on what I expected. Thanks for the awesome course!"

"Amazing Course Content... Every concept was explained well and it got more clear with the suitable examples. "

Instructor Reviews

Tarun Sukhani

IT Executive & Data Science Leader

"I attended one of Tarun's Data Science course in Jakarta (CDSS). He was a professional trainer & very knowledgeable in Data Science. In his course, Tarun gave many practical examples & valuable information regarding how to conduct Data Science & it's related components (e.g. Software & Deployment Architecture). In addition to those lessons, he also gave very useful insights on building a career as a Data Scientist."

"He shared his professional insights on data science with a sense of humor that cleared up so many of my questions about the content and real-world applications. Information, tools, and resources given are very useful"

"Tarun is very passionate on the domains and gave numerous insights to support critical business decisions and develop data products to transform daily encounters and processes. He was a professional trainer & very knowledgeable in Data Science. His material is presented through a sequence of brief lectures, interactive demonstrations, great hands-on exercises, and discussions."

"Tarun is the best Data Science lecturer you can find. He is experienced, knowledgeable and humorous, someone who is willing to share generously his working experience and knowledge in the field with the students. "

"Training with Tarun has been awesome. He’s super knowledgable, funny, empathetic and a great educator in general. As someone who didn’t come from a computer science background, his teachings didn’t make me feel stupid or impossible to eventually arrive at being a competent developer. I could understand him as he communicates well & has helped me see the big picture of the computer science field beyond the scope of syntaxes. If you similarly did not come from a CS background and hope to transition into the world of programming but struggle to learn on your own, understand all the foreign & abstract concepts and connect the dots, I think the right person to guide you on your journey would make a big difference. Having someone who’s deep in the field with many years of experience narrow and communicate the relevant areas to focus would also close a big gap from having to struggle and figure out a lot of things on your own. Being able to maintain your interest during your learning journey is important too, thus finding that someone is important. All in all, I would wholeheartedly recommend Tarun and the backend course I took."

"Tarun is a results-driven & inspirational technology leader with a clear vision, direction, and broad-based technology expertise. He is passionate, intuitive, engaged, pragmatic, systematic, agile. His experiences span from small start-ups to complex, global companies, from being technical lead to technical strategist to being the leader of larger group of architecture and engineering teams. Much of his experiences are in the area of Java, Scala, Machine Learning, Neural Networks, Cloud Computing, Data Science and what not. I am truly amazed to experience his breadth & depth of technological expertise and pleasure to be part of his team."

"He was indeed very skilled, knowledgeable and passionate in the data science realm. I was impressed with his business know-how (how the world economy works and how all things can be explain with data, with/without bias) and technical skills in converting data into insights. I will not hesitate to recommend Tarun for any data science related training as I would like to attend more classes myself to learn from the best of the best."

"We’ve been collaborated many times in doing courses for the accountants. He spoke to quiet number of event in our company with various topic regards to accountants need. The collaboration was very smooth and his session definitely made a huge impact on our success. Mr Tarun is a great Professional!"

"Mr. Tarun is a driven, hardworking, and knowledgeable entrepreneur in his field." A broad-minded trainer who embraces change and inspires people to do better every day. Mr. Tarun sets a good example by being enthusiastic and dedicated, and he inspires and motivates others. I am delighted to be working for such personnel"

"Attended "Blockchain Training: An Overview for Business Professionals" conducted by Dr. Tarun. The reference materials are very comprehensive and an excellent means of conveying information. I was very impressed with how this technology works and adapted into business"

FAQ

Frequently Asked Questions About This Course

What are the prerequisites for this Deep Learning for NLP course?

What practical skills will I gain from this course?

How is the course structured and what teaching methods are used?

What types of real-world applications will I work with?

Will I learn about the latest NLP technologies and models?

Does the course address ethical considerations in AI development?

Who is this course designed for and what career benefits can I expect?

Where is the training conducted?

Can international participants join this course?

What is the difference between public, corporate, and training provider pricing?

Do I have to pay right away?

I just enrolled in an intake. Does that mean I can attend the course on that date?

What happens if quorum for an intake is not reached?

Why should you attend?

What you'll learn

Develop proficiency in text preprocessing techniques including tokenization, stemming, and lemmatization.
Construct sequence to sequence models for machine translation and summarization.
Explore advanced topics like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for NLP tasks.
Recognize ethical considerations related to AI development in NLP.
Learn about word embeddings and their role in representing semantic relationships between words.
Understand the fundamental concepts of deep learning as they apply to NLP.
Build practical skills by creating sentiment analysis models using CNNs.
Implement transfer learning using state-of-the-art pre-trained language models for various NLP tasks.

Course Syllabus

Day 1 - Deep Learning Fundamentals

Module 1

Module 2

Short Break

15 mins

Module 3

Module 4

Recap and Q&A

15 mins

Lunch

1 hour

Module 5

Module 6

Short Break

15 mins

Module 7

Module 8

Recap and Q&A

15 mins

End of Day 1

Day 2 - Text Preprocessing Techniques

Module 9

Module 10

Short Break

15 mins

Module 11

Module 12

Recap and Q&A

15 mins

Lunch

1 hour

Module 13

Module 14

Short Break

15 mins

Module 15

Module 16

Recap and Q&A

15 mins

End of Day 2

Course Reviews

"A great course for anyone looking to dive deeper into NLP. Overall pretty well structured. But, a little bit difficult if you are not brushed upon the basics beforehand. "

"Very clearly articulated. A lot of concepts explained, really accurate and hit the mark on what I expected. Thanks for the awesome course!"

"Amazing Course Content... Every concept was explained well and it got more clear with the suitable examples. "