Job-Ready AI/ML Live Training
Budget: $750 – $1,500 AUD
I need a complete, beginner-friendly training program that takes absolute newcomers and turns them into job-ready practitioners across three pillars of modern machine learning: Natural Language Processing, Computer Vision, and Predictive Analytics. Everything must be delivered through live online sessions so students can ask questions in real time and work through hands-on exercises as a group.
Here’s what I’m expecting from you:
• A structured curriculum that steadily builds from zero knowledge to employment-level competence in each focus area.
• Live session slide decks, annotated notebooks or scripts, and any datasets you plan to use, shared ahead of each class.
• Practical projects after every major module so learners leave with portfolio-worthy work.
• Brief quizzes or checkpoints to confirm concepts have landed.
• Recordings of the sessions for later review.
Plan to weave in popular toolchains—think Python, scikit-learn, TensorFlow or PyTorch, Jupyter, plus the usual NLP and vision libraries—while keeping explanations clear, jargon-light, and immediately actionable. By the end, attendees should feel confident discussing model choices, training and evaluating them, and deploying simple prototypes.
If you have run similar live cohorts before, let me know the approximate class size you’re comfortable with and share a sample agenda or feedback from past participants. I’m ready to start as soon as the outline and calendar are agreed.
Here’s what I’m expecting from you:
• A structured curriculum that steadily builds from zero knowledge to employment-level competence in each focus area.
• Live session slide decks, annotated notebooks or scripts, and any datasets you plan to use, shared ahead of each class.
• Practical projects after every major module so learners leave with portfolio-worthy work.
• Brief quizzes or checkpoints to confirm concepts have landed.
• Recordings of the sessions for later review.
Plan to weave in popular toolchains—think Python, scikit-learn, TensorFlow or PyTorch, Jupyter, plus the usual NLP and vision libraries—while keeping explanations clear, jargon-light, and immediately actionable. By the end, attendees should feel confident discussing model choices, training and evaluating them, and deploying simple prototypes.
If you have run similar live cohorts before, let me know the approximate class size you’re comfortable with and share a sample agenda or feedback from past participants. I’m ready to start as soon as the outline and calendar are agreed.