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100-hour roadmaps, recorded masterclasses, structured mini-courses, and downloadable PDFs — all free. Three quick details once, and every resource unlocks.
The way we analyze data has changed forever. AI isn't just a tool anymore — it's your co-analyst, pattern finder, and insight engine. In this live masterclass, you'll discover how to combine the power of AI with core data analysis skills to work faster, think deeper, and deliver results that actually matter. Whether you're using Excel, SQL, Python, or Power BI — AI multiplies everything you already know. What you'll walk away with: ✅ How to use AI to clean, explore, and interpret data in minutes ✅ Real-world prompts and workflows for ChatGPT, Copilot & more ✅ Hands-on techniques used by top data professionals ✅ How to stand out in today's AI-driven job market This isn't theory. This is a live, practical session built for analysts, students, and professionals who want to stay ahead. Seats are limited. Register now and transform the way you work with data.
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The complete, domain-agnostic roadmap for recent graduates and course-completion students who want to land their first job organically — no paid placement, no fluff. Built for the new reality of 2026 hiring: ATS-screened CVs, AI-aware recruiters, the 60-30-10 networking shift, and AI tools you can use to put yourself ahead of 90% of candidates. What's inside: • Section 1 — The 2026 job market reality — what's changed since 2020, the 5 hard truths, ATS vs human screening, hidden job market • Sect
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A 16-page reference for every working professional, job-holder, or curious learner who wants to understand AI from scratch but doesn't know where to start. No prior tech background needed. No hype, no jargon — just the conceptual map of modern AI explained in plain language. What's inside: • Section 1 — What is AI, really? — the honest definition, ANI / AGI / ASI, the nested terminology (AI ⊃ ML ⊃ Deep Learning ⊃ GenAI ⊃ LLMs), the timeline that actually matters • Section 2 — The AI landscape —
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The complete working reference for AutoCAD — built as the companion to Phase 1 of the 100-hour BIM Engineer Roadmap. This 19-page document covers every command, alias, drawing aid, and modify tool an AEC professional uses day to day. Designed to read once and keep open beside the screen. What's inside: • Interface & setup — workspaces, coordinate-input formats (Absolute / Relative / Polar / Direct), UNITS, LIMITS, file formats • Keyboard shortcuts — F1–F12 reference plus 60+ command aliases (L,
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The complete working reference for Excel in data analysis. Built as the companion to Phase 1 of the 100-hour Data Analyst Roadmap, this 16-page document covers every command, formula, shortcut, and method an analyst needs day to day — designed to read once and keep open beside the screen. What's inside: > • Foundations — workbook anatomy, cell references (A1/A$1/A$1/ A1), data types, Tables (Ctrl+T), named ranges > • Keyboard shortcuts — 60+ across Navigation, Selection, Editing, Data, Formattin
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The industry-tested route into BIM, distilled into a 100-hour plan. Built on NETTMS's experience delivering BIM consultancy under EPC contractors for CPWD and MHA projects — the same standards-based discipline that wins audits. What's inside: • Phase 1 — Drawings & BIM fundamentals (10 h): IS 696, SP 46, LOD, BIM dimensions • Phase 2 — Revit authoring, end to end (35 h): Architecture, Structure, MEP, families • Phase 3 — Coordination & federation (20 h): Navisworks, clash detection, ACC • Phase
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The fastest-growing engineering niche, distilled into a focused 100-hour path. Move beyond chatting with LLMs to building grounded RAG systems and tool-using agents that act in the real world. What's inside: • Phase 1 — LLM foundations (10 h): transformers, tokens, model selection • Phase 2 — Building with LLM APIs (15 h): prompting, function calling, structured output • Phase 3 — RAG systems (25 h): embeddings, vector DBs, chunking, reranking, RAGAS • Phase 4 — Agents — tools, planning, memory
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The disciplined 100-hour launchpad into data science. Built for analysts, students, and engineers ready to move from dashboards to models. Every phase is hour-budgeted to the topic level. What's inside: • Phase 1 — Math & Python refresher (15 h): linear algebra, calculus, probability • Phase 2 — Classical ML (25 h): scikit-learn, XGBoost, LightGBM, cross-validation • Phase 3 — Deep learning essentials (25 h): PyTorch, CNNs, transformers • Phase 4 — Pick a domain, go deep (20 h): NLP, computer vi
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The complete hour-budgeted path to launching an analyst career. Five phases, exact hour allocations, tools mapped to each topic — no more guessing how long it takes. What's inside: • Phase 1 — Foundations of Analysis (15 h): Excel, statistics, data literacy • Phase 2 — SQL for working analysts (15 h): JOINs, window functions, CTEs • Phase 3 — Python & Pandas (25 h): cleaning, reshaping, NumPy, Seaborn • Phase 4 — Dashboards that tell a story (20 h): Power BI, Tableau, DAX • Phase 5 — AI Copilots
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The complete Python notes our analysts + data scientists use to onboard. Covers variables, data types, control flow, functions, OOP, pandas, NumPy and a hands-on capstone — everything you need before stepping into AI work. Free, download once and keep forever.
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