From data to production ready AI model code

Do you want your AI team to be better and faster at developing AI projects while writing production-quality code? Are you exploring a new career path in data science, or are you looking for peers with whom to work together and refine your skills in AI and coding?
This is the course for you! Even if you are from a business background, you will learn about the end-to-end AI development process to better collaborate with your technical colleagues.
In this 5-week course, we will take you through a range of lessons spanning from data wrangling to AI code optimisation. Designed by TurinTech’s researchers, the course brings together academic rigour with industry best practices.
As an added advantage, you will have the opportunity to try out TurinTech’s AI-powered code optimisation platform, evoML.

No prior knowledge of evoML is needed to complete this course.

Introduction to Machine Learning

Upstream: Data Gathering, Preparation

Learning: Supervised, Unsupervised, Reinforcement Learning & Time Series

Building: Model Training & Evaluation

Downstream: Model Deployment, Serving, Monitoring & Maintenance

Quiz: Machine Learning Life-Cycle

49 questions

Watch the Webinar video

Uncover Gems in your dataset with Feature Engineering

Introduction to Feature Engineering

Feature Improvement

Feature Generation

Feature Selection

Conclusion and References

Quiz: Basics of feature engineering

15 questions

Watch the Webinar video

Empower that model: a time-series tale

Introduction to forecasting

Forecasting with AR, MA and ARMA

Non-Stationary Series: SARIMA and Exponential Smoothing

Data Splitting and Leakage

Quiz

15 questions

Let your model speak via Explainability

Interpreting and Evaluating a Model

Explainability and Model Agnostic Methods

Explaining Neural Network Models

Using Explainability to Make Decisions

Quiz: Explainable AI

Automatic Code Optimisation of ML Models

Introduction to Efficient Code Design

Concept: Tracking ML Code Performance

Concept: Inference using the ONNX & TVM Framework

Quiz: Code Management and Deployment