Master Trainer - AI Skills

Role & responsibilities

Training Delivery

• Deliver engaging and informative lectures and workshops both online and offline. Adapt teaching strategies based on the mode of delivery and student feedback.
• Use a combination of classroom teaching, presentations, simulations, and physical demonstrations.
• Supervise students during lab-based practicals, ensuring adherence to safety procedures and effective learning outcomes.

Student Mentoring and Evaluation

• Design and administer assessments, case studies, and project work to evaluate student understanding and application of course materials. Provide one-on-one mentoring to students on their projects to tackle real-world scenarios.
• Offer mentoring to help students refine their projects and make them more competitive in the job market.
• Handle all program related concerns of the students.
• Provide constructive feedback on student performance and help with job-readiness preparation

Content Development

• Research and integrate the latest resources, tools, and case studies into the curriculum. Develop new content that reflects advances in technology and sustainability.

Office Tools

• Utilize a strong understanding of Microsoft Office tools (Word, Excel, PowerPoint, Outlook) to teach students practical applications relevant to their professional roles. • Integrate Office tools into training activities to enhance students' technical proficiency and productivity.

Reports

• Maintain accurate and comprehensive records of student progress, course updates, and teaching materials.
• Regular reports submitted to all relevant stakeholders and program management and plans for upcoming workshop/training
• Identify success stories in the region and will make them available, in a timely manner, to the top management for the showcase.

Technical Skills

• Strong Python programming skills and familiarity with AI-related libraries (NumPy, Pandas, Matplotlib, seaborn, Scikit-learn).

• Practical Hand on Experience on Machine Learning, Deep Learning Frameworks (TensorFlow, Keras, PyTorch).

• Desirable experience with Green Technologies like Renewable Energy Systems, environmental sensing technologies, resource management and other related field including their design, implementation, and optimization using AI.

• Knowledge of Generative AI, Large language models and their applications.

• Skills to work effectively in multidisciplinary teams, often necessary in projects that integrate AI and environmental science, and ability to communicate complex concepts to non-experts.

• Understanding the ethical implications of technological interventions in natural systems and the social impacts of deploying new technologies.

Soft Skills

• Excellent communication and instructional skills.

• Ability to explain technical topics in a depth and engaging manner, suitable for Engineering level learners.

• Strong classroom management skills and patience when dealing with learners from diverse backgrounds.

• Proficiency in local language

• Good verbal and written communication skills

• Advanced knowledge of MS Excel and Power BI Desktop, Service, Power

Preferred Qualifications (Preferred but Not Mandatory)

• Certification in Artificial Intelligent, Machine Learning, Data Science, Generative AI, Deep Learning, Python Programming, Big data

• Prior experience as a trainer or Professor, Assistant Professor in Degree Engineering College.
• AI/ML Trainer or Relevant Experience