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Jake
- Rate UGX 227,406
- Response 17h
-
Students1
Number of students Jake has accompanied since arriving at Superprof
Number of students Jake has accompanied since arriving at Superprof
UGX 227,406/hr
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- Maths
- Physics
- Computing
Machine Learning, Physics, and Math Tutor — Learn from an ML Researcher with 6+ years of Industry Experience
- Maths
- Physics
- Computing
Lesson location
About Jake
I’m a machine learning researcher with a background in physics and a deep passion for helping others understand how the world — and our algorithms — truly work. I’ve spent the last several years developing generative models and scientific AI systems that bridge quantum mechanics, mathematics, and computation. Along the way, I’ve discovered that my favorite part of research isn’t just the discovery itself — it’s the moment of understanding when a complex idea finally clicks for someone. I bring both academic depth and real-world experience to my teaching. I’ve led research projects in materials science and artificial intelligence, and I’ve mentored students from high school through graduate level in subjects ranging from classical mechanics to neural networks. My lessons are patient, structured, and highly personalized — designed to meet each student exactly where they are, and to build genuine confidence in problem-solving. Whether you’re preparing for exams, strengthening fundamentals, or diving into advanced topics like data science or deep learning, I’m here to make learning both clear and enjoyable. My goal is simple: to help you think like a scientist, code like an engineer, and see beauty in the logic that connects it all.
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About the lesson
- Primary
- Secondary
- Tertiary
- +6
levels :
Primary
Secondary
Tertiary
University
Adult Education
Masters
PhD (Doctor of Philosophy)
MBA
Early childhood education
- English
All languages in which the lesson is available :
English
✦ Teaching Approach My approach as a tutor is grounded in curiosity, clarity, and connection. I teach students not just what to learn, but how to think like a scientist and engineer. Whether we’re exploring quantum mechanics, training a neural network, or debugging a tricky Python function, the goal is always the same: to build intuition from first principles and confidence through understanding. I emphasize conceptual clarity first — turning abstract equations into mental pictures, and code into stories about how systems evolve and interact. Once the student grasps the essence, we move into applied problem solving, where I demonstrate how the same core ideas reappear across physics, mathematics, and machine learning. ✦ Teaching Method & Techniques Socratic guidance — I ask questions that guide students to discover the answer themselves, strengthening retention and insight. Visualization & analogy — I use diagrams, code demos, and real-world analogies to make complex ideas tangible. Iterative learning — Each concept is revisited through progressively more sophisticated examples — from analytic to computational to creative applications. Project-based learning — When appropriate, I help students design small projects (e.g., simulating a pendulum in Python, or training a simple neural net) that tie together theory and practice. ✦ A Typical Lesson Plan Warm-up (5–10 min) – Quick review of prior material; identify key challenges. Conceptual Focus (20–30 min) – Dive deep into one core concept using visual intuition and analogies. Applied Practice (20–30 min) – Solve targeted problems or write short code snippets together, discussing reasoning at every step. Integration (10–15 min) – Connect today’s topic to larger frameworks (e.g., symmetry in physics, generalization in ML). Reflection & Next Steps (5 min) – Recap insights, assign practice or readings for independent exploration. ✦ What Sets Me Apart I’m not just a tutor — I’m a practicing researcher in machine learning and physics, and I teach with the mindset of someone who lives these subjects daily. I help students develop intuition across domains — seeing how the logic of mathematics underlies the behavior of physical systems, and how both inform the intelligence of modern AI models. Students describe my lessons as both intellectually rigorous and deeply engaging — a mix of clarity, patience, and curiosity that makes even difficult topics feel natural and alive. ✦ Who My Lessons Are For High school students exploring advanced math, physics, or Python programming. Undergraduate or graduate students studying physics, computer science, or engineering who want to deepen their understanding or accelerate research skills. Professionals or researchers transitioning into machine learning, scientific computing, or data science who want personalized, conceptual guidance.
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Rates
Rate
- UGX 227,406
Pack prices
- 5h: UGX 1,137,029
- 10h: UGX 2,274,058
online
- UGX 227,406/hr
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