Instructor-led IT courses across web, mobile, data, design and more.
Many customers still pick up the phone when something is urgent, yet call centres struggle to answer in peak hours and staff repeat the same answers all day. The latest voice AI speaks Thai far more naturally and replies almost instantly, but building a voice…
Once staff in every department start using AI, organisations tend to hit the same problems. Each team signs up for a different service and holds its own API keys, nobody knows the total cost, customer data or confidential documents can be sent out by…
Good prompts and RAG solve a lot of problems, but some tasks need more. You may want a model that always answers in your organisation's format, uses domain terms correctly, classifies Thai documents accurately, or lets a small in-house model replace a large…
Every organisation has documents that someone re-keys every day: invoices, tax invoices, receipts, application forms and contracts, often arriving as scanned PDFs or phone photos. Traditional OCR struggles with Thai and has no idea which number is the net…
Many organisations want to use LLMs on internal documents, customer data or source code, but the rules say that data must not leave for an outside provider. The answer is to run open-weight models on the organisation's own machines or servers. Once a team…
Generative AI work in organisations today goes well beyond calling a language model API. Teams that build chatbots, document summarisers or search over internal knowledge need to understand everything from machine learning basics, tokenisation and…
Architects, engineers, contractors and quantity surveyors spend a great deal of time on documents: reading tender terms of reference, writing specifications, preparing and checking bills of quantities, comparing quotations and writing progress reports. This…
UX and UI work now has to move faster at every step, from synthesising user interviews to producing prototypes that let the team and clients see the idea. AI tools can draft surveys, cluster insights, generate screens from a description and build clickable…
Many master's and doctoral students, lecturers and researchers have started using AI to help with literature searches and writing. The problems that come up most often are AI producing references that do not exist, summaries that misstate the original paper,…
Hospital staff spend a great deal of time on work that is not direct patient care: letters, memos, meeting minutes, appointments, duty rosters, quality documents and answering questions from service users. Generative AI can reduce the time this paperwork…
Project managers spend a large share of their time on paperwork: drafting project charters, breaking down work, keeping risk registers, writing up meetings and producing weekly status reports, which leaves less time for decisions and for looking after people.…
Many organisations have already opened AI tools to their staff, yet real use tends to stay with a handful of people, while most employees do not know where to start, worry about data security, or tried once, got poor results and gave up. A single training…
Teachers and lecturers spend a great deal of time preparing lesson plans, making materials, setting tests, marking and handling administration, leaving less time for their students. Generative AI tools such as Gemini, ChatGPT, NotebookLM and Canva AI can…
Public sector work involves a large volume of documents that are produced again and again: official letters, internal memos, meeting minutes, performance reports and replies to citizens. Generative AI tools such as ChatGPT, Gemini, Copilot and NotebookLM can…
Chat-based AI assistants answer questions well, but they still wait for us to open the app and type a request every time. Routine work such as summarising the morning's email, reminding us of appointments, following news on topics we care about or tidying the…
Sound is a key part of today's content: voice-over in short videos, company podcasts, announcements, training materials and music for ads. Hiring voice talent, booking a studio or licensing music every time costs both time and money. AI audio tools can…
Slides and infographics take up a surprising share of the working week: boiling long reports down to the key points, laying pages out neatly in the corporate style, and drawing diagrams an audience can grasp in seconds. The latest AI tools can produce a whole…
Short video has become the main medium for marketing and internal communication, yet every shoot needs a crew, a location and a budget. The latest AI video tools let small teams create ads, animated product shots and explainer videos from text and still…
AI agents are moving beyond chatbots that only answer questions towards systems that plan, call tools and carry out multi-step work on people's behalf. Once teams start building them, though, the same questions keep coming up: how to split work across several…
Every organisation keeps its knowledge in manuals, reports, slide decks and meeting notes, yet finding an answer still means opening one file after another. Meanwhile everyday work such as repair requests, equipment checks and approvals still runs on paper,…
Many organisations already use Microsoft 365 Copilot for everyday work. The next step is building their own AI agents that know the organisation's data, answer questions from internal policies and documents, and take action on people's behalf, such as opening…
Many organizations have already invested in data and AI, yet their leaders still struggle to say where to start, which projects are worth funding and how to keep the risks under control. Conversations with technical teams are full of jargon, while decisions…
ChatGPT has become a tool many people open every working day, yet most still use it one question at a time. Today it can read files, analyze data, produce Word, Excel and PowerPoint files, connect to email and calendars, carry out in-depth research and run…
When an AI agent has to work through dozens of steps, call real tools, edit real files and run commands on real systems, what makes it trustworthy is not the model alone but the harness, the runtime wrapped around the model. That means a loop that knows when…
