Fine-Tuning ChatGPT for Your Business with Custom Data Sources

Master the art of fine-tuning ChatGPT for your business with our specialized training program. Learn how to extend capabilities using LlamaIndex, manage OpenAI credits efficiently, and create tailored solutions.

Online Jan 26, 2026 9:00 AM - 5:00 PM Mohammad Mehdi Lotfinejad
updated
intermediate
Fine-Tuning LLMs for Your Business
We price match

Public Pricing

MYR 1750

Corporate Pricing

Pax:

Training Fees: MYR 6500/day
Total Fees: MYR 6500 ++

Training Provider Pricing

Pax:

Training Fees: MYR 2800/day
Material Fees: MYR 600
Total Fees: MYR 3400 ++

Features

1 day
8 modules
20 intakes
Full life-time access
English
Technical: 25 pax

Target Audience

students
engineers

Methodologies

lecture
slides
labs
case studies
group discussion

Subsidies

HRDC Claimable logo

What you'll learn

  • Demonstrate adding custom data sources to enhance ChatGPT's functionality
  • Guide through indexing and querying processes using LlamaIndex configurations
  • Introduce LlamaIndex as a means to connect ChatGPT with custom data sources
  • Understand ChatGPT's history, advantages, disadvantages, and limitations
  • Teach efficient management of OpenAI credits and token usage
  • Learn how to manually extend ChatGPT via prompt engineering
  • Equip with strategies for further optimization of ChatGPT

Why should you attend?

This course delves into the intricacies of fine-tuning ChatGPT to cater to specific business needs. Participants will gain insights into what ChatGPT is, its historical development, and the inherent advantages and disadvantages it presents in a business context. The course emphasizes the importance of custom data sources and provides an overview of ChatGPT's capabilities and limitations. Learners will explore methods for extending ChatGPT manually through prompt engineering and context awareness, while also understanding the limitations of manual interventions. A dedicated section introduces LlamaIndex, a tool that enhances ChatGPT's functionality by connecting it to custom data sources, thereby outlining its benefits. The practical aspects of the course include adding custom data sources, utilizing LlamaIndex with GPT 'text-davinci-003', and creating a Q&A chatbot using pre-existing documents. Additionally, participants will learn about indexing and querying with LlamaIndex configuration, including loading Google Docs, managing indices, configuring prompt settings, and changing language models explicitly using the langchain package. Finally, the course covers monitoring OpenAI credits and token usage to optimize operational efficiency. The concluding module encourages learners to consider further exploration avenues and optimize ChatGPT utilization with custom data sources for enhanced performance.

Course Syllabus

Day 1
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

Instructor

Loading...
Mohammad Mehdi Lotfinejad Chief Data Officer & Data Science Trainer
Trainer Profile
Trainer Profile
TTT Certificate
TTT Certificate
Mohammad Mehdi Lotfinejad is a distinguished Chief Data Officer and certified HRDF trainer with over 15 years of experience in computer science instruction and professional data science training. Currently serving as Chief Data and Knowledge Officer at Magna.ai, a Florida-based lawtech company, he leads the development of sophisticated graph databases, data warehouses, and API solutions that power AI-driven legal case analysis systems. His expertise spans the entire data ecosystem, from architecture design to workflow automation and team leadership. With a robust background encompassing more than a decade of hands-on experience in data engineering and data science, Mohammad has successfully implemented enterprise-scale data processing pipelines across multiple industries and geographies. His professional journey includes senior roles at Axiata Digital Advertising (ADA) in Malaysia, where he designed and deployed data pipelines using AWS Redshift, Snowflake, Apache Spark, and Apache Airflow, and at The Center of Applied Data Science, where he led teams delivering training solutions to major corporations including CIMB, PETRONAS, SHELL, and TNB. Mohammad's technical proficiency is comprehensive and current, encompassing cloud platforms (AWS, Google Cloud), data warehousing solutions (Redshift, Snowflake), big data technologies (Apache Spark, Hadoop, Hive), workflow orchestration (Apache Airflow), and multiple database systems (MySQL, PostgreSQL, MongoDB). He holds a Harvard Business School certification in Business Analytics and multiple AWS certifications, including specialized credentials in Big Data, Data Warehousing, and Practical Data Science with Amazon SageMaker. As an educator, Mohammad brings exceptional depth to his training delivery. His academic career includes faculty positions at Payame Noor University and Islamic Azad University, where he served in leadership roles including Chancellor and Department Head. He has authored three technical books and published numerous peer-reviewed papers in international journals. His teaching repertoire covers data engineering, data science, machine learning, software development, and computer architecture, delivered through engaging, hands-on methodologies that bridge theoretical concepts with practical industry applications. Mohammad's unique combination of executive leadership, technical expertise, and proven training capabilities makes him an invaluable resource for organizations seeking to develop their data science and engineering capabilities. His ability to translate complex technical concepts into actionable learning outcomes, coupled with his extensive real-world implementation experience, ensures that training participants gain immediately applicable skills that drive business value.
8 Students
96 Courses
18 Years

Instructor Reviews

ML

Mohammad Mehdi Lotfinejad

Chief Data Officer & Data Science Trainer

"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."

"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."

"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."

FAQ

Frequently Asked Questions About This Course

Why should you attend?

This course delves into the intricacies of fine-tuning ChatGPT to cater to specific business needs. Participants will gain insights into what ChatGPT is, its historical development, and the inherent advantages and disadvantages it presents in a business context. The course emphasizes the importance of custom data sources and provides an overview of ChatGPT's capabilities and limitations. Learners will explore methods for extending ChatGPT manually through prompt engineering and context awareness, while also understanding the limitations of manual interventions. A dedicated section introduces LlamaIndex, a tool that enhances ChatGPT's functionality by connecting it to custom data sources, thereby outlining its benefits. The practical aspects of the course include adding custom data sources, utilizing LlamaIndex with GPT 'text-davinci-003', and creating a Q&A chatbot using pre-existing documents. Additionally, participants will learn about indexing and querying with LlamaIndex configuration, including loading Google Docs, managing indices, configuring prompt settings, and changing language models explicitly using the langchain package. Finally, the course covers monitoring OpenAI credits and token usage to optimize operational efficiency. The concluding module encourages learners to consider further exploration avenues and optimize ChatGPT utilization with custom data sources for enhanced performance.


What you'll learn

  • Demonstrate adding custom data sources to enhance ChatGPT's functionality
  • Guide through indexing and querying processes using LlamaIndex configurations
  • Introduce LlamaIndex as a means to connect ChatGPT with custom data sources
  • Understand ChatGPT's history, advantages, disadvantages, and limitations
  • Teach efficient management of OpenAI credits and token usage
  • Learn how to manually extend ChatGPT via prompt engineering
  • Equip with strategies for further optimization of ChatGPT

Course Syllabus

Day 1
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

Instructor Reviews

Mohammad Mehdi Lotfinejad

Mohammad Mehdi Lotfinejad

Chief Data Officer & Data Science Trainer

"Mehdi and I worked on several projects with company such as Petronas , Shell and CIMB Regional ETC. I must say Mehdi's training was highly appreciated by our clients as he was able to exhibit in full display his vast knowledge as a Data professional. I would highly recommend him to anyone looking for a top tier training expert."

"Not only knowledgeable but also having hands dirty on what he knows Friendly and building networks quickly."

"I had the pleasure of working with Mehdi together on some high-level initiatives such as the Petronas data scientist program and Shell's project to become a data-driven organization. During these projects, Mehdi received numerous accolades for his ability to share his knowledge and mentor up-and-coming data scientists. Based on our shared experiences, I have no hesitation in recommending Mehdi for any project or position he may be considered for."

We price match

Public Pricing

MYR 1750

Corporate Pricing

Pax:

Training Fees: MYR 6500/day
Total Fees: MYR 6500 ++

Training Provider Pricing

Pax:

Training Fees: MYR 2800/day
Material Fees: MYR 600
Total Fees: MYR 3400 ++

Features

1 day
8 modules
20 intakes
Full life-time access
English
Technical: 25 pax

Target Audience

students
engineers

Methodologies

lecture
slides
labs
case studies
group discussion

Subsidies

HRDC Claimable logo

Instructor

Loading...
Mohammad Mehdi Lotfinejad Chief Data Officer & Data Science Trainer
Trainer Profile
Trainer Profile
TTT Certificate
TTT Certificate
Mohammad Mehdi Lotfinejad is a distinguished Chief Data Officer and certified HRDF trainer with over 15 years of experience in computer science instruction and professional data science training. Currently serving as Chief Data and Knowledge Officer at Magna.ai, a Florida-based lawtech company, he leads the development of sophisticated graph databases, data warehouses, and API solutions that power AI-driven legal case analysis systems. His expertise spans the entire data ecosystem, from architecture design to workflow automation and team leadership. With a robust background encompassing more than a decade of hands-on experience in data engineering and data science, Mohammad has successfully implemented enterprise-scale data processing pipelines across multiple industries and geographies. His professional journey includes senior roles at Axiata Digital Advertising (ADA) in Malaysia, where he designed and deployed data pipelines using AWS Redshift, Snowflake, Apache Spark, and Apache Airflow, and at The Center of Applied Data Science, where he led teams delivering training solutions to major corporations including CIMB, PETRONAS, SHELL, and TNB. Mohammad's technical proficiency is comprehensive and current, encompassing cloud platforms (AWS, Google Cloud), data warehousing solutions (Redshift, Snowflake), big data technologies (Apache Spark, Hadoop, Hive), workflow orchestration (Apache Airflow), and multiple database systems (MySQL, PostgreSQL, MongoDB). He holds a Harvard Business School certification in Business Analytics and multiple AWS certifications, including specialized credentials in Big Data, Data Warehousing, and Practical Data Science with Amazon SageMaker. As an educator, Mohammad brings exceptional depth to his training delivery. His academic career includes faculty positions at Payame Noor University and Islamic Azad University, where he served in leadership roles including Chancellor and Department Head. He has authored three technical books and published numerous peer-reviewed papers in international journals. His teaching repertoire covers data engineering, data science, machine learning, software development, and computer architecture, delivered through engaging, hands-on methodologies that bridge theoretical concepts with practical industry applications. Mohammad's unique combination of executive leadership, technical expertise, and proven training capabilities makes him an invaluable resource for organizations seeking to develop their data science and engineering capabilities. His ability to translate complex technical concepts into actionable learning outcomes, coupled with his extensive real-world implementation experience, ensures that training participants gain immediately applicable skills that drive business value.
8 Students
96 Courses
18 Years

FAQ

Frequently Asked Questions About This Course

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