Introduction to Artificial Intelligence Trainer at Corporate Staffing

Roles and Responsibilities

Mobilisation and Training

• Mastering the Digital Content and Curriculum and planning lessons to Train Diverse Youth effectively.
• Mobilizing through communities and other avenues to invite Youth to benefit from the free Training e.g. through pitches, activations or exhibitions of the Program.
• Organizing and delivering quality Virtual Training and ensuring an 80% completion rate for registered Youth undertaking the Training.
• Planning and Researching on Training scope accordingly and understanding the audience needs during Training.
• Developing relatable examples and case study material for use to make training useful and exciting.
• Assessing objectively, against pre-set criteria, the ability levels of the learners as appropriate.
• Overseeing the learners in performing practical activities related to online work, advising and assisting where necessary, and ensuring that maximum learning benefit is gained from the practical experience.
• Ensuring good attendance tracking and providing daily reports on each Training session by marking attendance as per reporting template.
• Assess individual and group Training needs and provide recommendations.
• Adapt delivery of course material to meet the needs of the learners
• Conduct Training of Trainers (ToTs)

Mentorship and Work Linkages

• Conduct mentorship for each trained cohort as per the mentorship guidelines
• Assess the level of skill acquisition of the mentees
• Ensure active participation of all the mentees in the mentorship sessions
• Submit weekly reports on the progress of each cohort being mentored.
• Organize and coordinate job linkages webinars for the trainees
• Link the trainees/mentees with  work opportunities
• Report on impact stories from the trainees

Technical skills required

• Bachelor’s degree or diploma in a relevant field.
• 2+ years of working experience in the Artificial Intelligence field.
• Machine learning: Expertise in machine learning algorithms, such as supervised and unsupervised learning, reinforcement learning, deep learning, and neural networks.
• Programming: Strong proficiency in programming languages like Python, Java, R, and C++ is essential for building AI models and implementing algorithms.
• Natural language processing (NLP): Knowledge of NLP techniques, including text classification, sentiment analysis, and named entity recognition, necessary for developing intelligent chatbots and language processing systems.
• Computer vision: Familiarity with computer vision techniques, including image recognition, object detection, and facial recognition.
• Data analytics: Proficiency in data analytics tools like SQL, Tableau, and Apache Spark necessary for processing and analyzing large datasets.
• Mathematics and statistics: A strong foundation in mathematical concepts like linear algebra, calculus, and statistics is critical for developing and evaluating AI models.
• Algorithm design and optimization: The ability to design and optimize algorithms crucial for improving the efficiency and accuracy of AI models.
• Cloud computing: Knowledge of cloud computing platforms like AWS, Google Cloud, and Azure necessary for deploying and scaling AI models.
• Software engineering: Understanding software engineering principles like version control, testing, and deployment for building and maintaining robust AI systems.
• Big data technologies: Knowledge of big data technologies like Hadoop, Apache Spark, and NoSQL databases necessary for processing and analyzing large datasets used in AI applications
• Understand the utilization of Artificial intelligence skills in online work and possess the ability to train youths on the avenues of selling Artificial intelligence skills with a focus on earning a decent income from digital opportunities and platforms.

Closing: 2nd May 2023