Beginner AI/ML Trainer Needed

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@nrajuu07

I’m an AI/ML Engineer with 6+ years of experience, and I’ve also worked on Machine Learning and NLP tutoring projects. I enjoy teaching beginners and usually keep the sessions very practical, starting with simple explanations and then moving into small Python and scikit-learn examples so students can understand the ideas by actually using them. I can structure the programme from data preparation and supervised learning fundamentals through model training, evaluation, model selection and validation, with short introductions to unsupervised learning and neural networks where useful. I can also prepare class notebooks or slides, simple coding exercises, quizzes and recap notes for each session. My teaching style is interactive and beginner-friendly, with plenty of examples, questions and hands-on practice rather than long theory-heavy lectures. I’m available for weekday sessions and can share a clear session-by-session plan before we begin.

@innovateNsolve

Hello, I am a researcher and trainer in computer vision, machine and deep learning having PhD in Computer Science with 25+ years of experience. I have worked on several research projects in these domains with few research publications as well. I have strong theoretical knowledge with hands-on experience in AI/ML, Computer Vision, python, OpenCV, Tensorflow, PyTorch, MATLAB etc. I have extensive experience in delivering online sessions on AI/ML with hands-on demonstrations and for the targeted audience as working professionals and students. I have recorded live sessions on my channel. Hope to have further discussions in this regard to know more. Thanks.

@manishashree12

Hello there, I am excited about the opportunity to guide beginners in AI/ML fundamentals through your weekday program. I will develop a structured session plan with interactive classes covering data preparation, model selection, and supervised learning. Utilizing platforms like Zoom, I will provide engaging slide decks, code examples in Python, and quizzes for reinforcement. My experience in teaching AI/ML concepts to newcomers, along with a learner-focused approach, ensures a solid foundation for participants. Can we discuss further to align on the start date and class schedule? Thanks, Manisha

@PrateekP3003

The tricky bit here is pacing for absolute beginners - if you dive into scikit-learn too fast, people freeze on the math and quit. I'd keep each 2-hour session split: ~40 min intuition (why supervised vs unsupervised, what a model actually 'learns'), then a live Jupyter notebook they run alongside me, then a small quiz to lock it in. Supervised gets the weight - regression, classification, train/test split, evaluation metrics - with quick neural-net intuition only where it clears things up. I build ML systems day to day, so the code examples come from real work, not textbook toys. What week are you looking to start, and roughly how many learners per cohort? - Prateek

@areebat90

HellOOOOO there , I’d be happy to lead this beginner-friendly AI/ML programme. I’m an Applied AI Engineer with hands-on experience building and explaining AI systems using Python, machine learning, NLP, RAG, and LLM-based applications. I enjoy breaking complex technical concepts into simple, practical steps that beginners can understand and apply. For this programme, I can provide: * Live 2-hour interactive sessions, Monday–Friday * A structured session-by-session curriculum focused on AI/ML fundamentals and supervised learning * Jupyter notebooks with simple Python + scikit-learn examples * Hands-on exercises, quizzes, and short assignments * Recap notes/recordings to help learners revise * Practical demonstrations connecting theory to real-world AI applications My teaching style is highly practical and interactive: explain the concept, demonstrate it, let students implement it, and then solve a small problem themselves. I’d be happy to share a detailed weekly plan and discuss the schedule and milestones.

@sara0346

Hello, I reviewed your project for teaching absolute beginners AI and ML fundamentals. Python with Jupyter and scikit learn will keep lessons practical and easy to follow. I will structure sessions around data preparation, supervised learning, model training, evaluation and simple hands on exercises, with notebooks, quizzes and recap material for each class. The training will focus on clear explanations and practical learner progress. Best Regards, Sara

@abhilashr53

I can deliver 'Beginner AI/ML Trainer Needed' end to end — clean architecture, tests, and deployment. I'll start with a short plan, share progress daily, and hand over production-ready code. Could you confirm your timeline and must-have features so I can lock the scope?

@abdurrehman373

Teaching complex technical concepts like AI/ML to beginners requires balancing deep subject matter expertise with a structured, approachable pedagogy. I specialize in Full-Stack development and Python, and I have a strong background in simplifying technical workflows for others to follow. My approach to your programme: - Week 1 Foundations: Focus on data preparation, cleaning, and the logic of supervised learning using Python and scikit-learn. - Interactive Delivery: I use Jupyter Notebooks for live-coding sessions, ensuring students see code execute in real-time. I break down mathematical concepts into intuitive, visual explanations. - Resource Creation: I will provide structured slide decks, clean code snippets, and short, outcome-based assignments to ensure daily progression. I am comfortable with remote delivery tools and can structure a curriculum that keeps absolute beginners engaged without overwhelming them. While I am newer to this specific platform, my professional background in building complex MERN/Python applications allows me to teach the 'why' behind the code, not just the syntax. I am available to start immediately and am happy to draft a session-by-session syllabus once we discuss the exact duration of the course. Let's discuss your preferred time slot.

@nolanf7

I’d structure the programme around a practical learning path: Python/Jupyter setup → data preparation → features/labels → train/test split → supervised learning → regression → classification → model selection → evaluation metrics → overfitting → basic unsupervised learning/neural-network intuition. Each 2-hour class would combine a short concept lesson, live coding, guided exercises, questions, and a small assignment or quiz. Students would receive runnable Python + scikit-learn notebooks, simple examples, recap notes/recordings, and progressively more challenging exercises. My teaching style focuses on explaining why a technique is used, then letting learners implement it themselves rather than simply watching code being written. The outcome I’d target is that a beginner can take a small dataset, prepare it, select an appropriate supervised model, train it, evaluate the result, identify common problems such as overfitting, and explain what they built. I can work within your ₹1,500–₹3,500/day teaching range. Could I prepare the first week’s session-by-session outline and notebook structure for your review?

@handysolver

Designing a 2-hour daily Supervised Learning curriculum for absolute beginners requires stripping away matrix calculus bloat and focusing immediately on interactive, scikit-learn pipelines. I can deliver a turnkey 2-week live training program equipped with runnable Google Colab/Jupyter notebooks, clear slide decks, daily micro-quizzes, and recap guides tailored specifically for beginner retention. ### Proposed Teaching & Delivery Strategy 1. **Curriculum Design & Scaffolded Pedagogy** * **Week 1: Foundations & Core Supervised Algorithms** (Data Cleaning, Feature Scaling, Linear/Logistic Regression, Decision Trees). * **Week 2: Model Tuning & Real-World Application** (Train/Test Splits, Overfitting/Underfitting, Cross-Validation, Metrics like Precision/Recall/F1, and a simple Unsupervised/Neural Network visual teaser). 2. **Interactive Live Format (2 Hours/Day)** * **First 45 Mins:** Concept breakdown using intuitive visual analogies (e.g., housing price predictions for linear regression). * **Next 50 Mins:** Live collaborative coding—students follow along in pre-configured Google Colab notebooks. * **Final 25 Mins:** Q&A, micro-assignment breakdown, and concept recap. 3. **Turnkey Student Assets** * Daily executable `.ipynb` code notebooks (with 'fill-in-the-code' exercises). * Modular slide decks PDF/PPT and 1-page summary cheat-sheets for each session. * Automated Google Forms quizzes (5 questions per session) for quick skill verification. ### Relevant Experience & Successes As a Senior AI Instructor and Lead Engineer, I have trained over 400+ absolute beginners across live bootcamps and corporate upskilling programs. My teaching style is hands-on, code-first, and highly encouraging. In my last 4-week intro cohort, 92% of non-technical participants successfully built and evaluated their first classification pipeline independently by the end of week two. ### Proposed Schedule & Milestones (10 Sessions / 2 Weeks) * **Milestone 1 (Week 1 - 5 Daily Sessions):** Curriculum Outline + Slides/Notebooks + Live Delivery (Data Prep & Core ML Models) | ₹12,500 * **Milestone 2 (Week 2 - 5 Daily Sessions):** Advanced Evaluation + Hyperparameter Tuning + Final Capstone Project Guidance | ₹12,500 Let's jump on a quick Freelancer chat to finalize your start date, target duration, and preferred class timings so I can share a sample session outline immediately.

@patodeh

Designing a live, beginner‑level AI/ML training program that covers supervised learning fundamentals across daily two‑hour Zoom sessions is the core requirement. I will create a detailed week‑by‑week agenda, develop slide decks and Jupyter notebooks for each class, and provide concise Python scikit‑learn code examples that students can run locally. I will include short assignments that reinforce data preparation, model selection, training, evaluation and the distinction between supervised and other learning paradigms, with occasional intuitive demos of unsupervised methods and neural‑network concepts. All materials will be production‑ready, clearly documented and aligned with the agreed schedule. To ensure the curriculum matches your expectations, could you confirm the total number of weeks you plan for the program? I will set up the full teaching package, coordinate the delivery platform and be available for any real‑time adjustments. Let’s chat, lock in the exact scope and get started.

@Snorgletast

Hello — I can help with this scoped request: Beginner AI/ML Trainer Needed. I’m setting up a weekday programme for absolute beginners who want to break into Artificial Intelligence,Machine Learning, MERN Full Stack, DevOps . You will run live, interactive classes for two hours each day, Monday through Friday, with the primary goal of giving students a rock-solid grounding in AI/ML basics—especially supervised learning. Format & schedule • 2 hr live session, five days a week (Mon–Fri) • Start date and exact time slot to be agreed together • Remote delivery via Zoom, Google Meet or a comparable platform Core content Students must leave the course confident in the fundamentals: data preparation, model selection, training & evaluation, and how supervised learning differs from other paradigms. Feel free to weave in brief demos of unsupervised methods or neural-network intuition when it helps beginners see the bigger picture, but the emp I will confirm the exact inputs and acceptance criteria, complete only the agreed scope, and verify the final artifact against those criteria before delivery. I will identify any missing information rather than inventing it, and I can provide a concise evidence/quality summary with the result. If that approach fits, please share any source files and the required format.

@Sahilh77

Hi, I’d be a strong fit for this programme because I have around 5 years of hands-on experience in Python, AI/ML, Data Science, and software development, and I enjoy breaking technical concepts into practical, beginner-friendly examples. I can conduct the 2-hour live sessions with a hands-on approach rather than making the classes purely theoretical. Students can learn a concept, see a practical example, and then implement it themselves using Python, Jupyter, NumPy, Pandas, and Scikit-learn. I can cover data preparation, supervised vs. unsupervised learning, regression, classification, model selection, training, evaluation metrics, overfitting, and practical ML workflows. I can prepare a structured session-by-session curriculum along with Jupyter notebooks, simple code examples, slides/notes, assignments, quizzes, and recap material. I’ll keep the mathematics approachable and focus on helping absolute beginners understand why a technique is used before showing them how to implement it. I can also briefly connect the fundamentals to Neural Networks, Deep Learning, MERN, and DevOps where useful, giving students a broader understanding of the AI/technology landscape without losing focus from the core ML curriculum. I’m comfortable delivering classes remotely through Zoom/Google Meet and can start according to your preferred schedule. Best regards, Sahil

@GenomyR

Hi, Regarding your project (Beginner AI/ML Trainer Needed): I can develop and integrate the system cleanly using AI & LLM Integration and Python / Django / FastAPI, built for robust rate-limiting, error handling, and low-latency responses. My delivery approach: 1. Stage 1 (50% Milestone): Model pipeline architecture, prompt/schema definitions, and sandbox API integration within 2-3 business days. 2. Stage 2 (50% Milestone): Guardrails testing, response streaming UI, and production deployment with full documentation. Which specific LLM provider or external APIs will this system interface with? Best regards, Tumisang

@mohammedsayahr

Hello, As a Computer Science Engineer holding a Master's degree, I specialize in Machine Learning and Python-based data architecture. I have hands-on, practical experience teaching and building AI/ML solutions using Python, Scikit-learn, and Jupyter Notebooks. I am fully prepared to lead your 2-hour daily live sessions (Mon–Fri) to guide beginners through supervised learning. Here is what I will provide for the program: 1. Structured Session Outline: Clear daily progression from raw data preprocessing to model evaluation. 2. Interactive Class Materials: Complete Jupyter Notebooks, slide decks, and clean, runnable Python code examples. 3. Daily Assessments: Short, practical quizzes and quick exercises to reinforce core concepts. 4. Comprehensive Support: Class recaps and guided practice to build solid learner confidence. My teaching style focuses on making complex mathematical and algorithmic concepts intuitive for complete newcomers. I am available immediately for your preferred time slot via Zoom or Google Meet. Looking forward to collaborating with you! Best regards, Rouas Mohammed State Engineer in Computer Science

@KeshavVerma4403

Hi, I'd love to help run this program. I have a strong academic foundation in AI/ML (specialization coursework covering supervised learning, model evaluation, and NLP fundamentals) along with hands-on project experience — including a customer behavior analysis project and a toxic comment detection ML model, both built end-to-end from data prep to evaluation. I also built a full BI platform (Streamlit + AWS RDS + EC2) for a client's business, so I'm comfortable explaining real, working systems rather than just theory. I don't have formal bootcamp/university teaching experience, but I've led as VP of my college's tech/music club, mentoring and coordinating with members regularly, so I'm used to breaking things down for people at different levels and keeping sessions structured and engaging. My teaching approach for absolute beginners: keep concepts intuitive first (analogies before math), pair every idea with a runnable code example, and reinforce with short quizzes/assignments so nothing feels passive. Happy to share a sample session outline before we finalize anything if that helps you evaluate fit. Looking forward to it.

@Appworldz

Hi, I enjoy teaching beginners because the challenge isn’t showing code—it’s making the concepts finally click. I’ve delivered hands-on technical training covering AI/ML, Python, scikit-learn, Jupyter and practical software development. I’d structure the programme around short explanations, live coding, visual intuition and exercises: data preparation → supervised learning → model selection → training → evaluation → mini-project, with just enough unsupervised/NN context to connect the dots. Each day I can provide a notebook/slides, runnable examples, quiz/homework and recap notes. Rate: ₹5,000/day for the 2-hour session. Mon–Fri | 5 days/week

@pushpender0at

My bid of ₹1,250 is a Week 1 trial rate. If my sessions, slides, and student engagement meet your standard — and they will. I'm happy to move to your budgeted range from Week 2. Zero risk on your end.