Training & Upskilling
Practical, instructor-led sessions that build real AI capability inside your team. Each workshop is hands-on, grounded in engineering contexts, and adaptable to your data and systems.
This workshop gives engineering managers and senior technical staff a clear, grounded understanding of modern AI and machine learning. Participants explore how contemporary models work, what they can and cannot do, and how to evaluate feasibility, data needs, risks and ROI. The session blends intuitive explanations with practical examples so leaders walk away able to guide AI-related decisions with confidence rather than buzzwords.
This hands-on session walks participants through the full lifecycle of a machine learning project, from problem framing and data preparation to model training, evaluation and deployment. The emphasis stays on practical engineering workflows using reproducible tools. By the end, attendees will have built a simple but complete pipeline and will know how to adapt the same structure to their own industrial problems.
This workshop introduces foundational image processing techniques and modern computer vision workflows. Participants work with real data to understand filtering, feature extraction, segmentation and classification using classic methods and deep learning. The goal is to make image-based analysis feel intuitive and operational so engineers can diagnose where vision solutions fit into their systems.
This session explores practical multimodal learning where images, text, vibration data or time-series measurements work together. Participants analyze how to encode each modality, how to design fusion strategies and how to evaluate models that operate across heterogeneous inputs. The emphasis is on real engineering contexts such as predictive maintenance, quality inspection and automation.
This workshop shows how to transform unstructured text into engineering-relevant insights. Participants learn how to use embeddings, retrieval, classification, summarization and domain-tuned models to extract patterns from reports, logs, maintenance notes and documentation. The session focuses on workflows that augment existing engineering processes rather than replacing them.
In this session participants learn how to run language models locally or on controlled infrastructure so proprietary or regulated data never leaves their environment. The workshop focuses on practical setup, model selection, optimization, prompting and evaluating outputs with an emphasis on privacy, reproducibility and compliance. Engineers leave with a working local LLM environment and the skills to extend it safely.
Every session can be tailored to your industry, data, and skill levels. Reach out to plan a private workshop for your organization.
For any inquiries please contact us at contact@appliedin.co.