AI Trainer/Mentor Needed – Beginner to Job-Ready AI, Machine Learning & Generative AI

@ZohaibRoy

⭐⭐⭐⭐⭐ Personalized AI Training for Job-Ready Skills ❇️ Hi My Friend, I hope you are doing well. I reviewed your project requirements and see you are looking for an AI trainer/mentor. You have no need to look further; Zohaib is here to help you! My team has successfully completed 50+ similar projects in AI training. I will provide structured, one-on-one sessions that cover AI fundamentals, machine learning, and generative AI, all while ensuring hands-on experience through real projects. ➡️ Why Me? I can easily deliver your AI training as I have 5 years of experience in AI and machine learning, focusing on beginners. My expertise includes practical project development, AI ethics, and hands-on mentoring. I also have a strong grip on tools like Python, Jupyter, and various AI platforms to enhance your learning experience. ➡️ Let's have a quick chat to discuss your goals in detail. I can show you examples of my previous work and training methods. Looking forward to speaking with you! ➡️ Skills & Experience: ✅ Artificial Intelligence ✅ Machine Learning ✅ Generative AI ✅ Large Language Models ✅ Prompt Engineering ✅ AI Development ✅ Python Programming ✅ AI Ethics ✅ Career Mentoring ✅ Project-Based Learning ✅ Resume Building ✅ Interview Preparation Waiting for your response! Best Regards, Zohaib

@Mahihassi

As a multitalented and experienced Electrical Engineer with a Master's in Embedded Systems, I offer a unique combination of talents for your AI training project. My expertise includes firmware development, PCB design, and complete IoT product engineering. In line with your requirements, I am also highly proficient in AI, Machine Learning (ML), and Deep Learning as I have been utilizing these technologies to create intelligent algorithms for edge devices, control systems, and data analysis. Furthermore, my proficiency extends to Robotics & Control, Biomedical Instrumentation and Emerging Tech( specifically Blockchain & Web3 apps). As such, I posses a solid understanding of the underlying hardware that powers AI systems. This allows me to explain complex concepts of artificial intelligence utilizing simple language. When it comes to teaching beginners, I have established my abilities through my extensive career. Not only have I trained junior engineers on multiple platforms but i have also written blog posts and conducted webinars on AI/ML introductory content. This experience has honed my ability to teach such topics effectively and build curriculums tailored specifically for each stage of the learning process.

@intelliresponse

Hello, I can help you build a structured AI learning path from fundamentals to practical, job-ready skills. I understand that you are looking for personalized mentoring rather than a simple course, so I will focus on clear explanations, hands-on exercises, real projects, and continuous feedback. I can guide you through AI fundamentals, machine learning, Python, deep learning concepts, Generative AI, LLMs, prompt engineering, embeddings, vector databases, RAG systems, and AI agents. The learning process can include practical projects such as building an AI knowledge assistant, automation workflows, and real-world ML applications that can become portfolio pieces. My approach is beginner-friendly and project-focused. I will help you understand concepts deeply, review your code and projects, improve your technical skills, and prepare you for AI-related job opportunities through resume guidance, portfolio improvement, and interview preparation. I have practical experience with AI/ML development, Python, LLM applications, RAG architectures, and AI automation solutions. I can provide a personalized roadmap, regular mentoring sessions, practical assignments, and guidance to help you progress from beginner level to confidently building and explaining AI solutions.

@corpmember29

Hello, AI Trainer/Mentor {{{ I HAVE 11+ YEARS OF EXPERIENCE IN AI, MACHINE LEARNING, PYTHON AND GENERATIVE AI, AND I CAN GUIDE YOU FROM BEGINNER TO JOB-READY LEVEL }}}} I read your requirements carefully and understand that you need practical, personalized one-to-one mentoring rather than pre-recorded courses. I can structure the learning journey from AI/ML fundamentals and Python to Generative AI, LLMs, Prompt Engineering, RAG, Vector Databases, AI Agents and API-based applications. We will follow an Agile, hands-on approach with live sessions, assignments, regular feedback and 2–3 portfolio-quality projects such as a RAG knowledge assistant, AI agent/automation and practical ML solution. I can also assist with resume/CV improvement, GitHub and LinkedIn presentation, realistic AI career paths, technical interview preparation, mock interviews and job-search strategy. I will tailor the curriculum according to your current programming level and focus on understanding concepts clearly while building real-world projects. I eagerly await your positive response. Thanks

@denisSolution

Hi, I'm Denis, a full-stack developer with hands-on experience building AI and generative AI systems. I've worked on RAG implementations, LLM integrations, AI agents, and machine learning projects, and I've mentored several people transitioning into AI roles. I understand you need someone who'll guide you through building real projects, review your work, and help you prepare for interviews with genuine confidence—that's exactly what I provide. Here's my approach: I'll create a personalized roadmap covering AI fundamentals, machine learning essentials, and generative AI focused on job-relevant skills. Each week combines live sessions explaining concepts clearly, hands-on exercises between sessions, and detailed feedback on your work. We'll build 2-3 portfolio projects together—starting with a RAG-based chatbot, then moving to an AI agent or ML solution. I'll teach you Python, Jupyter, LangChain, vector databases, and APIs like OpenAI and Azure. On the career side, I'll help refine your resume, conduct mock technical interviews with feedback, and guide your job search strategy. Typically, 8-12 weeks at 8-10 hours per week gets someone to job-ready status. This works when there's consistent effort. I can start right away. Let's discuss the details. Thanks, Denis.

@TeraByte26

Hi Vaidyanathan, I will deliver a personalised AI→ML→Generative AI roadmap, live weekly one‑to‑one sessions, 2‑3 portfolio‑grade projects (RAG assistant, AI agent), updated resume, interview prep and job‑search strategy. Commit to completing the program within 12 weeks, 4 hrs/week, within your AUD 750 budget. I can start tomorrow with a free 30‑minute demo; let me know your preferred start day. Waiting for your response in chat! Best Regards.

@Aaleen110

You need an AI trainer to get you from beginner concepts to job-ready AI and ML skills, so I will start by mapping out the core modules we will cover. I will build this training program using Python and focus on practical application, so we will use libraries like Scikit-learn for core ML tasks and TensorFlow or PyTorch for deep learning concepts, whatever makes the most sense as we progress. We will cover AI fundamentals, how modern systems work, real-world use cases, and the entire lifecycle from data to inference, also touching on responsible AI as we go. The brief leaves underspecified how much hands-on project work you want, so I will assume a mix of guided coding exercises and a capstone project that simulates a real-world problem. Track record on here: 100% on time, 100% on budget, 5.0 across 8 reviews. What is your current programming experience level? Let's schedule a short call on Freelancer to settle the scope, covering your specific learning goals and the pace we will set for the training.

@Hubready

Hello!, I am a US-based senior software engineer and I’d be a strong fit for this. Your real challenge is not just learning AI, but getting from beginner to job-ready with a clear path, hands-on practice, and the confidence to use what you learn in real work. That’s exactly how I mentor. I’d approach this in practical phases: 1. Assess your current level and define a clear roadmap 2. Build strong Python, ML, and AI fundamentals 3. Move into prompt engineering, LLMs, RAG, and AI agents with guided exercises 4. Turn theory into mini projects that are portfolio-ready 5. Review progress regularly so you always know what to focus on next I’ve built production AI systems, automation, and data pipelines, so I know what matters beyond tutorials. My focus would be helping you understand the “why” behind the tools, and then applying it in a way that’s useful for interviews, projects, and real-world work. Could you please clarify the following questions to help me better understand the project? 1. What is your current level in Python and machine learning? 2. Are you aiming for AI engineering, ML, data science, or applied AI/automation? 3. Do you want a fixed learning plan or a flexible mentor-style approach? Relevant work includes AI support assistants, RAG knowledge base tools, Python automation systems, and LLM-powered research helpers. I’d be glad to make this structured, practical, and tailored to your goals. James Zappi

@muhammadali33345

Hi , I’ve reviewed your AI Trainer/Mentor Needed – Beginner to Job-Ready AI, Machine Learning & Generative AI requirements and I can help you complete this successfully. I have strong hands-on experience with Generative AI, AI Model Development, Python, AI Development, AI Consulting, Machine Learning (ML), AI Agents, Retrieval-Augmented Generation (RAG), AI Strategy and LLM Prompt Engineering and have worked on similar projects before. I can start immediately and will deliver a clean, reliable, and fully tested solution according to your requirements. Let’s discuss the project in chat — I can get started right away. Regards, AA

@shrec

Hi, I’d be happy to structure this as a personalized, hands-on AI learning program rather than a collection of prerecorded tutorials. The progression I’d recommend is AI fundamentals first, then Python and core ML concepts, followed by Generative AI, LLMs, embeddings, RAG, agents, and AI APIs. The practical side would be central to the training. We could build 2 to 3 portfolio projects such as a RAG knowledge assistant, an AI agent/automation workflow, and a machine learning project using a real dataset. I’d review your work during each stage and adjust the pace based on your programming background. I can also include resume and GitHub project positioning, interview preparation, mock interviews, and a practical job-search strategy. I’d suggest starting with 4 to 6 hours per week and targeting roughly 12 to 16 weeks for a solid job-ready foundation, depending on your starting point. Best, Ivane

@AndrewJSMAN

I've built production ML pipelines and shipped LLM applications across classification, RAG, and agent workflows—so this is right in my wheelhouse. I'll structure the engagement as: Python fundamentals + scikit-learn/pandas → supervised/unsupervised learning with real datasets → LangChain + OpenAI/HuggingFace for LLMs, prompt engineering, embeddings, and RAG systems → 2–3 portfolio projects (knowledge assistant, classification model, AI agent). Each module includes hands-on exercises, code review, and iteration cycles to lock in concepts before moving forward. On the employment side, I'll review your resume against actual job descriptions, run two mock technical interviews with scenario-based questions, and map realistic roles based on what we've built. I typically recommend 8–10 weeks at 6–8 hours weekly for job-ready depth—live sessions only, no pre-recorded material. The risk I watch for is knowledge gaps during transitions between concepts, so I validate understanding through working code and project output, not just discussion. I can start immediately and outline the roadmap after an initial sync on your current Python level. Thanks, Andrii.

@razmiks2

Hi, I have 10+ years of experience building production AI systems with Python, Generative AI, and AI Development. I’ll create a structured AI Fundamentals, Machine Learning Fundamentals, and Generative AI pathway with hands-on exercises that build toward 2-3 portfolio projects, including RAG and AI agents using Python. I’ve mentored beginners through practical project work and interview-ready portfolios with actionable feedback. Best, Razmik

@mayr81

Structured one-to-one AI mentoring for beginners, focused on job-ready outcomes. Build clarity from fundamentals (AI concepts, responsible AI, ML supervised/unsupervised, evaluation basics) through hands-on Generative AI (LLMs, embeddings, vector databases, RAG, agents, API workflows, security and limitations). You’ll work through guided exercises, assignments, and mini-projects at every stage, not lecture-only learning. The plan culminates in 2-3 portfolio-quality projects such as a RAG-based knowledge assistant, an AI automation/agent workflow, and a practical ML solution built on real datasets with reproducible notebooks. Career support is integrated throughout: an AI-focused CV refresh, targeting realistic roles, GitHub/portfolio presentation guidance, and technical plus scenario-based interview practice. Deliverables include a personalized AI→ML→Generative roadmap, supporting notes/resources, and two mock interviews with detailed feedback to strengthen performance. Approach for limited programming experience: explain concepts in plain language, ramp Python gradually using notebooks (Jupyter/Colab-style workflow), and ensure every concept maps to a working artifact you can demonstrate to employers. Regular live sessions and direct feedback keep progress consistent and measurable.

@carlosd178

Hello, As a result of a detailed review of your project requirements, I fully understand that you are looking for a hands-on AI mentor who can guide you from fundamentals to practical AI/ML and Generative AI skills with portfolio projects and career preparation. My approach would be a structured roadmap: • AI fundamentals → Machine Learning basics → Generative AI → Advanced LLM applications. • Practical work using Python, Jupyter/Google Colab, GitHub, AI APIs, LangChain-style frameworks, and vector database concepts. • Building portfolio projects such as a RAG knowledge assistant, AI automation agent, and practical ML application. For beginners, I focus on clear explanations first, then guided implementation. Each session would include exercises, code reviews, assignments, and feedback so the skills become practical rather than theoretical. I would also support resume improvement, GitHub/portfolio presentation, interview preparation, and realistic AI career planning based on your progress. I have a couple of quick questions. • What is your current programming level (beginner, intermediate, or experienced)? • What type of AI career direction interests you most: AI developer, ML engineer, automation specialist, or AI consultant? I would be glad to discuss your learning goals and create a personalized roadmap. Looking forward to helping you build practical AI skills. Best regards, Carlos.

@RusianD

Hello, I’ve carefully reviewed the requirements and believe I’m a strong fit for the trainer and mentor role. I understand this is aimed at helping a beginner build practical LLM and prompt engineering skills, so I will keep the learning structured, hands on, and focused on skills that transfer directly to real projects and job opportunities. My plan is: Assessment: I will identify the current knowledge level and establish a practical learning path without unnecessary theory. Foundations: I will explain LLM concepts, tokens, context windows, prompting patterns, structured outputs, and common limitations with simple examples. Prompt Engineering: I will teach prompt design, system instructions, few shot prompting, evaluation, debugging, and techniques for improving reliability. Projects: I will guide practical exercises using real APIs and small applications rather than relying only on tutorials. Advanced Topics: I will introduce RAG, embeddings, vector databases, tool calling, agents, and workflow orchestration as skills progress. Mentoring: I will review work, explain mistakes, suggest improvements, and help develop independent problem solving habits. My experience includes OpenAI APIs, LLMs, RAG, LangChain, LangGraph, AutoGen, CrewAI, vector databases, Python, and AI agent development. Best regards, Ruslan

@C0RETECHIES

Hi there, Transitioning to a job-ready AI practitioner requires moving beyond theory into production pipelines. Your learning lifecycle will involve Python scripting, vector embeddings, LLM orchestration, and deploying multi-agent workflows to build a demonstrable GitHub portfolio. Technical approach: We use Jupyter for ML foundations, transitioning to VS Code for GenAI apps. We will utilize OpenAI APIs, LangChain, and vector databases (Pinecone), focusing on RAG architectures and low-code orchestration (n8n) to rapidly bridge programming gaps. Core modules: - ML Foundations: Python basics, classification, and model evaluation. - GenAI Implementation: Prompt engineering, API handling, and RAG. - Agentic Workflows: Multi-agent orchestration and tool calling. - Career Prep: Resume optimization, technical mock interviews, and job search strategy. Relevant systems: - Automation Lead Generator (8-Agent AI Pipeline) - AI-Powered Slack Assistant (LangChain/RAG) Implementation strategy: I recommend a 12-week roadmap (3 live hours/week). We will build a Document RAG Assistant and an AI Automation Agent. Having mentored numerous junior engineers, I translate complex math into practical engineering steps, ensuring you grasp the operational mechanics of real-world AI systems without getting stuck on early syntax issues. 1. What specific industry domain should we tailor your portfolio projects around? 2. Are we starting entirely from scratch with basic programming logic? 3. How many hours per week can you dedicate to assignments outside live sessions? Regards, Rohit

@mughiraaa

Hello, I have already worked on similar AI and Generative AI projects involving Python, machine learning, LLMs, RAG, AI APIs, agents, and scalable software solutions. I also have strong experience in web development and APIs. I can guide you from AI fundamentals through practical ML and Generative AI, using hands on exercises and real projects rather than only theory. We can also cover GitHub, portfolios, resume improvement, interview preparation, and mock interviews. Would you prefer starting with Python and ML fundamentals, or moving directly into Generative AI based on your current experience? I can quickly understand your level and create a practical learning path around your goals. Happy to discuss it in a quick meeting. I will share my portfolio in chat I look forward to hear from you. Thanks Best Regards, Mughira

@emilesd617

Hi, I am a full-stack AI developer with 8 years of rich experience in software development, with a strong background in Machine Learning, Generative AI, and practical AI application development. I am familiar with Python, Jupyter, scikit-learn, OpenAI, Azure OpenAI, Hugging Face, LLMs, prompt engineering, embeddings, vector databases, RAG, LangChain, AI agents, GitHub, model evaluation, and responsible AI. I recommend a structured AI fundamentals → Python/ML → Generative AI → RAG/agents journey, with hands-on exercises and 2–3 portfolio projects such as an ML prediction system, RAG knowledge assistant, and AI automation agent. For a beginner, I would focus on practical coding and simple explanations before gradually introducing deeper concepts. I can also support CV improvement, GitHub portfolio preparation, technical interview practice, mock interviews, and job-search preparation. I would recommend approximately 10–12 weeks at 6–8 hours per week, adjusted to your progress. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Thanks. Emile.

@SkillCrafts

Your goal of moving from AI fundamentals to job-ready practical skills resonates strongly with my experience in developing and delivering targeted AI upskilling programs. I've successfully guided individuals with zero prior knowledge through comprehensive curricula, culminating in tangible project portfolios and interview-ready confidence, much like the outcome you're seeking. My approach will involve a structured curriculum built around Python, leveraging libraries like Scikit-learn for foundational ML, TensorFlow/PyTorch for deep learning, and LangChain/Hugging Face for Generative AI. We'll progress through theory with hands-on coding exercises, followed by capstone projects such as building a sentiment analysis model, fine-tuning a small language model, or developing a basic image generation pipeline, ensuring practical application at each stage. To best tailor this plan, could you elaborate on your preferred learning pace and any specific domains within AI (e.g., NLP, Computer Vision) that are of particular interest? I’m available for a brief chat to discuss how we can achieve your objectives efficiently.