AI Academy Programmes

According to McKinsey, superior talent is up to eight times more productive. In the world of Artificial Intelligence, talent management is often difficult because of (i) challenges in hiring, and (ii) structuring the right roles and career path for individuals. Through our sessions, we help management understand what AI talent is looking for, and how to incentivize them with a well-planned career path that is aligned to the business objectives.

As a comprehensive approach to talent management, we also help teams get onboarded on speaking the AI language so as to integrate AI within the teams more seamlessly. RELUVATE is the only approved partner of AI Singapore (Singapore's official AI Programme) on AI trainings. We conduct bootcamps for AI capability certification to prepare individuals for full-fledge Machine Learning roles. Check out our 5 core programmes below, all sessions are customized for the needs of the participants. Get a headstart. schedule a session today

AI Singapore announced the launch of the AI Certified Engineer (AICE) programme on 9 April 2020. The certification programme aims to develop and recognize individuals' technical competency and experience in AI.

We are proud to be the first accredited certification partner of AI Singapore.
Our training is designed at the development needs of candidates to pursue AICE certification.
At the end of our training programme, we will coordinate with AI Singapore for the certification assessment of each candidate.

Certification level: Associate Engineer
Targeted at students who are deeply interested in coding /AI/ML, fresh graduates, working professionals who employ data analysis techniques in the course of their work

Format:
  • Lecture-based instruction
  • Complete coding assignments on own devices
  • Work through guided lessons and curated datasets
  • Facilitated discussions and sharing sessions
  • Final project and review
  • AI Singapore Certification test: Associate Engineer
Objectives:
  • AICE Associate Engineer certification
  • Gain proficiency Python, SKlearn, SQL, visualization packages
  • Master the use of control structures in algorithms
  • Learn basics of ML/AI, including ethics and governance
  • Build, train and test ML models on curated datasets (numerical and NLP)
  • Practicing AI reproducibility
  • Perform data exploration, cleaning, analysis on output
  • Learn best practices of ML engineer
  • End-to-end deployment
  • Ensure model robustness and maintainability
  • Work on business-related project to create minimal viable product/proof-of-concept


Certification level: AI Certified Engineer Level 1
Targeted at working professionals with a minimum of 1 year of working experience in AI-related roles. Individuals at this level are AI specialists in AI project teams in a commercial organization.

Format:
  • Lecture-based instruction
  • Complete coding assignments on own devices
  • Work through guided lessons and curated datasets
  • Facilitated discussions and sharing sessions
  • Reviewing research literature and critique
  • Implementing a live project worth > SGD250K
  • Final project and review
  • AI Singapore Certification test: AICE Engineer Level 1
Objectives:
  • AICE Level 1 Engineer certification
  • Able to define clear business problem statement
  • Confidence in processing various types of data (examples: tabular, image, sparse)
  • Explore a number of deep learning architectures
  • Model design and deployment at scale using python packages
  • Mastery in statistics and theoretical knowledge
  • Communication skills to both technical and non-technical stakeholders
  • AI ethics, biases and governance
Format:
  • Seminar-style lectures and interactive classrooms
  • Facilitated discussions and sharing sessions
  • Presentation and review
Objectives:
  • Understand implications of AI on businesses (general introduction to what AI is about)
  • Case studies of the impact of AI revolution (specific industry-based case studies, tailored to client’s industry, function, region)
  • Benefits of AI-enabled business units (discussion of viable areas of growth in company)
  • High-level planning of AI-transformation roadmap (presentation and review of discussion)
Format:
  • Seminar-style lectures with smaller breakout sessions
  • Facilitated discussions and sharing sessions
  • Immersive learning through basic coding session on web-based interface
Objectives:
  • Understand implications of AI on businesses (general introduction to what AI is about)
  • Build awareness of the current state of AI and its capabilities
  • Identify key technical skills required to develop inhouse AI technology
  • Study the workflow of AI projects and products
  • Gain proficiency basic AI techniques and its uses
Format:
  • Lecture-based instruction
  • Complete coding assignments on own devices
  • Facilitated discussions and sharing sessions
Objectives:
  • Gain proficiency Python to be “dangerous”
  • Master the use of control structures in algorithms
  • Write simple routines in Python
  • Use Python libraries
  • Perform data analysis
  • Automate processes
  • Understand impact of automating process management in the business
Format:
  • Lecture-based instruction
  • Complete coding assignments on own devices
  • Work through guided lessons and curated datasets
  • Facilitated discussions and sharing sessions
  • Project presentations and reviews
Objectives:
  • Gain proficiency Python and SKlearn
  • Master the use of control structures in algorithms
  • Learn basics of ML/AI
  • Build, train and test ML models on curated datasets (numerical and NLP)
  • Perform data exploration, cleaning, analysis on output
  • Learn best practices of ML engineer