
AI Trainer
1 week ago
AI Trainer
Role Overview: We are seeking a passionate and experienced AI Trainer to deliver foundational to intermediate-level AI and Python training as part of the Women in AI Initiative. The trainer will be responsible for mentoring learners from diverse backgrounds and guiding them through hands-on modules covering programming, data analysis, machine learning, cloud tools, and Generative AI.
Key Responsibilities:
• Deliver sessions on Python programming, data handling, supervised/unsupervised learning, and Generative AI.
• Design, update, and facilitate interactive practical labs, coding exercises, and capstone projects.
• Guide learners in problem-solving, data preprocessing, model evaluation, and interpretation
• Conduct career-readiness workshops including resume reviews, mock interviews, and LinkedIn optimization.
• Maintain learner engagement via tools like MS Teams, VS Code, GitHub, LinkedIn Learning, and Microsoft Learn.
• Provide constructive feedback and support to students throughout the 12-week learning journey.
Education & Qualifications:
• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
• Certification in AI/ML, Python, or cloud technologies (e.g., Microsoft Certified: AI Fundamentals) is preferred.
• Prior teaching or mentoring experience in a technical domain is highly desirable. Technical Skills Required: Programming & Data Handling:
• Strong hands-on knowledge of Python
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• Proficient with data structures: lists, dictionaries, functions, file handling
• Experience in NumPy, Pandas, and Seaborn for data analysis and visualization Machine Learning & AI:
• Understanding of Supervised Learning: linear & logistic regression, decision trees, SVM, KNN, model evaluation metrics
• Familiar with Unsupervised Learning: K-Means clustering, PCA, recommendation systems
• Ability to train and validate models using scikit-learn and visualize outputs Generative AI & Prompt Engineering:
• Familiarity with ChatGPT, prompt types (zero-shot, few-shot), and real-world applications
• Understanding of LLM risks such as bias, hallucination, and ethical implications Cloud & No-Code AI Tools:
• Exposure to Microsoft Cognitive Services, ML Designer, and drag-and-drop tools
• Experience with OCR, speech-to-text, and text analytics in a cloud setting is a plus Soft Skills & Additional Competencies:
• Strong communication and facilitation skills
• Passionate about diversity in tech and mentoring underrepresented groups
• Ability to explain complex concepts in a simple, relatable way
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