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In-depth courses on web scraping, anti-bot evasion, cybersecurity, and networking, plus learning roadmaps for engineers who value their time. No fluff, just the implementation.

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Web Scraping Cybersecurity Networking Anti-Bot Evasion

206 lessons 39 roadmaps 1124 articles

coursesall topics ->
Web Scraping 67 lessons A complete web scraping course: HTTP and parsing fundamentals, crawling, browsers, anti-bot engineering, and production-scale data pipelines. 01 HTTP Basics for Scraping02 Understanding HTML Structure03 requests, Sessions & Headers 67 lessons · free start ->
Cybersecurity 42 lessons Concepts, attack vectors, and defensive techniques for application and network security. 01 Encryption02 Hashing vs Encoding03 Digital Signatures and PKI 42 lessons · free start ->
Networking 35 lessons How data moves. Protocols, layers, and the infrastructure of the internet. 01 TCP/IP Model02 Ethernet, ARP & Switching03 IPv4 and IPv6 Addressing 35 lessons · free start ->
Anti-Bot Evasion 62 lessons Learn techniques for bypassing modern anti-bot protections, CAPTCHAs, and advanced fingerprinting. 01 How Anti-Bots Work02 The Defender's Signal Inventory03 IP Reputation & Proxies 62 lessons · free start ->
featured roadmapsall 39 roadmaps ->
Web Scraping 15 topics 01 Foundations02 Core Concepts03 Intermediate Skills 4 stages open roadmap -> Cybersecurity 16 topics 01 Foundations02 Offensive03 Defensive 4 stages open roadmap -> Frontend Development 40 topics 01 Internet Fundamentals02 HTML Fundamentals03 CSS Styling 8 stages open roadmap -> Backend Development 38 topics 01 Internet & OS02 Languages03 Relational Databases 8 stages open roadmap -> Python 116 topics 01 Foundations02 Core Concepts03 Intermediate Skills 29 stages open roadmap -> Machine Learning & AI 17 topics 01 Mathematics02 Fundamentals03 Deep Learning 4 stages open roadmap ->
latest newsall news ->
programming languages Oct 06 LLM-Complete: The next 700 programming languages Why Some Programming Languages Resist LLMs Programming abstractions have always been a trade-off between expressiveness and clarity. Dijkstra argued convincingly that good abstraction lets us think clearer, say what's needed unamb... ai Oct 06 Show HN: TOD,a universal Decision model based on Task Oriented Design Parseclab has released TOD, a small decision model that sits in front of an existing LLM and handles the turns it is confident about, deferring the rest. Built on an open 12-billion-parameter Gemma 4 base, TOD reads text and image... ai Oct 06 Mirror Particle is building a ‘world model’ of human behavior Startups promising to predict human behavior are attracting substantial venture funding. Over the past year, Simile raised $200 million at a $2 billion valuation, Aaru secured $88 million at a $1 billion valuation, and Humans& lau...
latest papersall papers ->
arXiv:2610.06852 Oct 06 One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipeline Shih-Chen Tseng, Chih-Hsuan Chen, Ryan Yang, Hsi-An Chen, Chun-Wei Tuan Mu, Yu-Lun Liu The Repurposing Problem in ML Pipeline Figures Machine learning papers rely on pipeline figures to communicate model architectures, data flows, and training procedures. A single diagram must serve multiple output formats: two-colu... arXiv:2610.06851 Oct 06 Base Models Can Reason By Taking a Cue From Training Data Sophie L. Wang, Amil Dravid, Rulin Shao, Kevin Farhat, Sewon Min, Alexei A. Efros The study of reasoning in base models has taken a surprising turn. Rather than relying on reinforcement learning to shape behavior, researchers have found that specific starting token cues can unlock reasoning capabilities already... arXiv:2610.06848 Oct 06 TranScope: What the Software Hides About LLM Training Data, the Hardware Reveals at Scale, and Accelerators Magnify Joshua Kalyanapu, Darsh Asher, Kaushal Mhapsekar, Bita Aslrousta, Rushiraj Chaitanyakumar Sheth, Maharshi Mukeshkumar Oza, Achyuta Kannan, Samira Mirbagher Ajorpaz The fundamental assumption that neural network inference can be made truly independent of training data has been called into question. Membership inference, the problem of determining whether a particular datum was part of a model...