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Raj Singh
10+ years in AI and Data Science | Machine Learning, Deep Learning, NLP, and Data Analytics | Helping students turn data into top grades
🗣️ Languages: English, Hindi
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Research Guidance
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Project Support
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About this expert
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Hello! I'm Raj Singh
Hello! I'm Raj Singh, an AI and Data Science expert with 10+ years of professional experience building intelligent systems, training predictive models, and delivering data driven insights. I help students and learners strengthen their understanding of Machine Learning, Deep Learning, NLP, and Data Analytics so they can confidently complete assignment help, homework help, project help, lab task help, and online class help with clear explanations and strong results.
I hold a Postgraduate Diploma in Big Data Analytics (2010) and have worked across end to end pipelines, from data preparation and feature engineering to model evaluation, deployment, and performance optimization. My goal is simple: help you master the concepts and apply them correctly, not just submit an answer.
AI and Data Science Expertise
My work covers both classic and modern AI techniques. I focus on practical, high ranking industry skills that directly map to university coursework and real world applications.
- ✅ Machine Learning (ML) for prediction, classification, and clustering
- ✅ Deep Learning with neural networks, training strategies, and evaluation
- ✅ Natural Language Processing (NLP) including text preprocessing and modeling
- ✅ Computer Vision for image based learning and analysis
I also support advanced topics and scalable data solutions that many students struggle with during deadlines.
- ✅ Reinforcement Learning fundamentals and implementation guidance
- ✅ Generative AI including GANs and Transformers
- ✅ Large Language Models (LLMs) concepts, prompting, and evaluation
- ✅ Big Data Analytics with Hadoop and Spark
Core Skills for High Scoring Submissions
When students request assignment help or project help, they usually need more than code. They need a complete learning package: correct methodology, clean implementation, and strong academic structure. I provide exactly that using proven workflows.
- 🧠 Supervised & Unsupervised Learning
- 🧩 Feature Engineering and data preparation
- 📊 Statistical Analysis for evidence based insights
- 🔍 Predictive Modeling with proper validation
- 💻 Python for Data Science
- 📚 R Programming
- 🗃️ SQL for Data Analysis
- 📐 Database Management for Data Science
- ⚙️ TensorFlow & Keras
- ⚡ PyTorch
- 🛠️ Scikit learn modeling and pipelines
- 🚀 MLOps and Model Deployment
What I Help You Deliver
No matter the level, I help you structure your work clearly and build credibility with correct evaluation metrics, reproducible code, and well organized documentation. This is especially valuable for homework help, lab task help, and online class help where clarity and correctness matter most.
- 📌 Assignment help with step by step explanations and final answers that match your rubric
- 📌 Homework help covering ML concepts, coding tasks, and interpretation of results
- 📌 Project help from problem definition to data pipeline, modeling, and reporting
- 📌 Lab task help with clean notebooks, correct experiments, and reproducible outputs
- 📌 Online class help for understanding lectures, implementing algorithms, and preparing for submissions
My Approach: Learn the Method, Not Just the Output
I teach the reasoning behind every technique you use. For example, if you are working on classification, we discuss data quality, train test split, metrics, and error analysis. If you are working on NLP or LLMs, we focus on preprocessing, embeddings, evaluation, and responsible usage.
- ✅ Clear problem statement and assumptions
- ✅ Correct data preprocessing and feature engineering
- ✅ Model selection with justification and validation
- ✅ Proper evaluation metrics and result interpretation
- ✅ Clean, well documented code and notebooks
- ✅ Reproducible steps for your submission
- ✅ Guidance on AI ethics and fairness where relevant
- ✅ Support for deployment and MLOps concepts when needed
Why Students Choose Me
I combine deep technical expertise with a student friendly teaching style. My focus is to help you build confidence, improve grades, and develop skills you can reuse in future courses.
- 🎯 Strong understanding of ML, Deep Learning, and Data Analytics topics that appear in exams and projects
- 🧾 Original, well structured work that supports learning and presentation
- ⏱️ On time delivery habits with clear progress communication
- 🧠 Explanations that help you understand evaluation, tradeoffs, and model behavior
If you want AI and Data Science help that is accurate, well explained, and aligned with your course expectations, I am ready to support you. Let’s work together to turn your data into decisions and intelligence.
Let’s work together!
Expertise areas
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Education & credentials
Academic background and certifications added to this expert profile.
Education
Postgraduate Diploma in Big Data Analytics
North Bethesda University
2010
Certifications
IBM Data Science Professional Certificate
IBM
2017
Student reviews
Feedback is shown only after moderation. New expert profiles may not have public reviews yet.
4.9
★★★★★
Based on 17 reviews
5 star
16
4 star
1
3 star
0
2 star
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1 star
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s
Verified Student
26-05-2026
★★★★★
Absolutely amazing work! The expert went above and beyond. I highly recommend this expert.
s
Verified Student
24-05-2026
★★★★★
Raj Singh outstanding final result quality.
Z
Verified Student
24-05-2026
★★★★★
Raj Singh very efficient and effective work.
s
Verified Student
24-05-2026
★★★★★
Great professionalism and patience Raj Singh.
s
Verified Student
22-05-2026
★★★★★
Excellent problem understanding and solution.
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Yes. You can share rubrics, PDFs, screenshots, datasets, code files, and other required documents during the hiring or chat process.
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Can I request changes after delivery?
Yes, you can request revisions based on your original requirements and feedback. Clear instructions help the team resolve revision requests faster.
What should I send before hiring?
Send the deadline, marking rubric, question file, expected format, word count or technical requirements, and any instructor notes.
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