Low-Code Data Scientist: Low-Code AI Apps including LLMs and ChatGPT (online)



Overview

“AI will not take your job - but someone who uses AI will” 

Over the last few months, with the advent of chatGPT, this maxim has become a reality.
Unlike the narrow AI that preceded it, chatGPT shows early characteristics of AGI (Artificial General Intelligence).

While AGI will create disruption, it also creates opportunities. Specifically, for the first time, the combination of LLM (large language models like chatGPT) and low-code development techniques allows non-developers familiar with IT to learn AI.  

This course is designed for people who work within the broader information technology ecosystem but are not necessarily developers. Hence, you need not have a coding/developer background for this course but need to be familiar with IT.

The course suits a range of personnel who want to understand artificial intelligence: business analysts, account managers, technical architects, data analysts, project managers, IT sales and pre-sales personnel media and PR, network, and systems administrators. 

The philosophy of this course is based on how to collaborate with generative AI (an AI co-pilot approach) primarily through prompt engineering.

This course explores how to create artificial intelligence applications (machine learning and deep learning applications) using low-code and large language models (LLMs), including ChatGPT.  

The course assumes no knowledge of AI, machine learning, or coding - but assumes that you work within the broader information technology ecosystem. We may demonstrate code in some sessions, but we will not expect you to code.

Upon completing this course, you should be able to build machine learning and deep learning applications using generative models and low-code.

Dates, Times and Delivery

The taught course will run from 17 June - 3 July 2024. 

Tutorials will be delivered via Microsoft Teams on Mondays, Wednesdays and Fridays from 14:00 - 18:30 (UK time) with a 30-minute break during this time period.

Session Dates:

  • Monday 17 June
  • Wednesday 19 June
  • Friday 21 June
  • Monday 24 June
  • Wednesday 26 June
  • Friday 28 June
  • Monday 1 July
  • Wednesday 3 July

A world clock, and time zone converter can be found here: https://bit.ly/3bSPu6D

Accessing Your Online Course 

Details about accessing the private MS Teams course site will be emailed to you during the week prior to the course commencing.  

Please get in touch if you have not received this information within three working days of the course start date. 

Programme details

Themes covered by the course include:   

  • Machine learning and deep learning concepts   

  • Machine learning and deep learning workflows 

  • Building blocks of low-code ecosystems    

  • An Introduction to large language models (LLMs)

  • Understanding Large language models and how LLMs differ from traditional application development.  

  • Understanding LLM modalities: code, images, language 

  • LLMs as an application development platform: Using low-code and LLMs, including ChatGPT, for developing AI applications 

  • Implementing the machine learning pipeline in low-code systems     

  • Prompt engineering  

  • The Azure low code platform in detail, including Azure Open AI integration 

  • Understanding the use of LLMs in AWS and GCP 

  • Deploying low-code and LMS AI services in cloud-native MLOps environments    

  • UX and integration for low-code    

  • Use of pre-built models and templates for creating AI applications   

  • Comparing and contrasting capabilities of low-code and full-code AI solutions    

  • Scaling low-code AI solutions   

  • Security and access for low-code applications   

  • Using code generation tools like GitHub Co-pilot  

  • Using generative tools in the creative space like DALL-E  

  • Examples of low-code applications 

  • Fine-tuning low-code models 

  • Ethical AI and Responsible AI Considerations for low-code and generative applications   

  • The overall end-to-end architecture of LLMs, including langchain and pinecone 

Considering the nature of the topic, the above may be subject to minor changes and adjustments. 

Digital Certification

To complete the course, you will be required to attend and participate in all of the live sessions on the course in order to be considered for a certificate. Participants who complete the course will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course.

The certificate will show your name, the course title and the dates of the course you attended. You will also be able to download your certificate or share it on social media if you choose to do so.

Fees

Description Costs
Standard course fee £1395.00

Payment

Fees include electronic copies of course materials.

All courses are VAT exempt.

Tutors

Ajit Jaokar

Course Director

Based in London, Ajit's work spans research, entrepreneurship and academia relating to artificial intelligence (AI) and the internet of things (IoT). 

Ajit is the Course Director and/or tutor for Continuing Education’s portfolio of artificial intelligence courses for professionals:

Ajit is also a Visiting Fellow in the Department of Engineering Science here at the University of Oxford.

He also works as a Data Scientist through his company feynlabs - focusing on building innovative early stage AI prototypes for domains such as cybersecurity, robotics and healthcare.

Besides the University of Oxford, Ajit has also conducted AI courses in the London School of Economics (LSE), Universidad Politécnica de Madrid (UPM) and as part of the The Future Society at the Harvard Kennedy School of Government.

He is also currently working on a book to teach AI using mathematical foundations at high school level. 

Ajit was listed in the top 30 influencers for IoT for 2017 along with Amazon, Bosch, Cisco, Forrester and Gartner by the German insurance company Munich Re.

Ajit publishes extensively on KDnuggets and Data Science Central.

He was recently included in top 16 influencers (Data Science Central), Top 100 blogs (KDnuggets), Top 50 (IoT central), and 19th among the top 50 twitter IoT influencers (IoT Institute). 

His PhD research is based on AI and Affective Computing (how AI interprets emotion).

Mr Jesus Serrano Castro

Speaker

Jesus is an accomplished digital industry professional with 25 years of experience, including the last 16 years at Microsoft.

He specialises in digital transformation, innovation, artificial intelligence, human-computer interaction, and user experience, while also maintaining a strong technical background as a software engineer.

He is a leader in emerging forms of interaction such as extended reality, voice, and biometric interfaces.

In 2014, he was the inventor of one of Microsoft's protected patents for a virtual experience applied to public events, long before the term "metaverse" became popular.

Throughout his career, Jesus has been involved in a wide range of industries, including retail (Zara, IKEA), banking (Santander), insurance (Reale), media (Sony Pictures, 20th Century Fox), and telecommunications (Ooredoo).

He has also led the Sports and Entertainment Innovation team, managing 180 sports organisations in 35 countries and 23 sports (Real Madrid, Real Sociedad, Laliga, FIFA, FIVB, IAAF, Toyota WRC, WWE, Russia World Cup 2018, Qatar World Cup 2022 etc).

He has led the development of several successful consumer apps for iOS, Android, Windows and HoloLens, which have received millions of downloads.

He is a top Microsoft speaker, having delivered over 100 sessions and keynotes at global events, achieving the Microsoft Speaker Grand Slam (speaking at the five largest Microsoft global events). He is also an Associate Professor in various Master's programmes and a frequent collaborator with business schools, universities and bootcamps.

Jesus' favourite quote is "Do not follow where the path may lead. Go instead where there is no path and leave a trail" - Ralph Waldo Emerson. 

Ms Ayşe Mutlu

Course Director

Data Scientist

Ayşe Mutlu is a data scientist working on Azure AI and devops technologies. Based in London, Ayşe’s work involves building and deploying Machine Learning and Deep Learning models using the Microsoft Azure framework (Azure DevOps and Azure Pipelines).

She enjoys coding in Python and contributing to Open Source Initiatives in Python.

Marina Fernandez

Speaker

Digital Hive and Innovation consultant, Anglo American Plc

Marina is an Analyst Developer and Software consultant at Anglo American Plc working at the Digital Hive on innovative trading analytics and optimisation projects.

She has over 18 years’ experience in Software Engineering, Business Analysis, Data Science and full software development life cycle in a variety of business domains including Commodity trading and optimisation, Finance, Machine Learning and Artificial Intelligence, e-commerce, e-learning, web-development.

Marina holds an MSc, with distinction, in Software Engineering from the University of Oxford and a degree in Applied Mathematics from Lomonosov Moscow State University. 

In February 2020, Marina completed the course "Data science for internet of things" from the University of Oxford.

Anjali Jain

Speaker

Digital Solutions Architect, Metrobank 

Anjali is a Digital Solutions Architect at Metrobank, where she helps to deliver advanced technology driven business solutions around diverse themes of Internet Banking, Mobile App, Business banking, and Open banking/PSD2, using agile methodology.

She has over 16 years of IT experience and worked across Banking, Telecom and logistics domains, from inception to the delivery of complex projects.

Anjali is passionate about AI and Machine learning and completed the course "Data science for internet of things" in February 2019 from the University of Oxford.

Christoffer Noring

Tutor

Senior Cloud Advocate, Microsoft 

Chris is Senior Cloud Advocate at Microsoft with more than 15 years in the IT industry.  He's a published author on several books about web development as well as the Go language.  He's also a recognized speaker as well as keynote speaker and holds a Google developer expert title.   

Application

Please use the 'Book' or 'Apply' button on this page. Alternatively, please contact us to obtain an application form.

Level and demands

For this course, no prior coding experience is needed but some technical industry background (non coding) or domain knowledge in a tech field is advisable. Our aim is to keep the course inclusive for people who do not have coding/low-code experience. However, if you are still unsure about the suitability of this course, please email us and we will answer any questions you have. We are also happy to arrange to speak to you.

IT requirements

This course is delivered online using Microsoft Teams. You will be required to follow and implement the instructions we send you to fully access Microsoft Teams on the University of Oxford's secure IT network.

This course is delivered online; to participate you will need regular access to the Internet and a computer meeting our recommended Minimum computer specification.

It is advised to use headphones with working speakers and microphone.

Terms & conditions for applicants and students

Information on financial support