Understanding Blockchain Chain Analysis

Free download скачать Understanding Blockchain Chain Analysis
Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.76 GB | Duration: 8h 16m
Blockchain Data Analysis for Everyone

What you'll learn
Understanding Blockchain Fundamentals
Proficient Data Extraction and Analysis
Blockchain Data Visualization
Detecting Anomalies and Security Threats
Real-World Application and Case Studies
Requirements
None
Description
This course is designed to provide a comprehensive understanding of blockchain technology and how to analyze blockchain data effectively. Students will learn about various blockchain platforms, data analysis tools, and techniques to investigate and interpret blockchain data. Unlock the power of blockchain data with our self-paced Blockchain Data Analysis Masterclass. Dive deep into the world of blockchain technology and become an expert in extracting, processing, and analyzing blockchain data. Whether you're a seasoned data analyst or a newcomer to the field, this course will equip you with the skills and knowledge to excel in blockchain data analysis.Course Highlights:Foundational Blockchain Education: Gain a strong foundation in blockchain fundamentals, including how it works, its components, and its applications.Practical Data Extraction: Master the art of data extraction from various blockchain networks and learn how to handle data from cryptocurrencies like Bitcoin and Ethereum.Data Visualization: Create captivating visualizations of blockchain data using industry-standard tools to communicate your insights effectively.Security and Anomaly Detection: Detect anomalies, security threats, and vulnerabilities in blockchain data, and learn how to conduct security audits on smart contracts.Real-World Application: Apply your knowledge to real-world case studies and projects, solving complex problems in areas such as transaction tracing, fraud detection, and compliance checks.Why Choose This Course?Self-paced learning allows you to tailor your studies to your schedule.Engaging content and hands-on projects.Access to a supportive community and an experienced instructor.Blockchain data analysis skills are in high demand in various industries.Become a blockchain data analysis expert and embark on a journey into one of the most revolutionary technologies of our time. Join our Blockchain Data Analysis course today and gain a competitive edge in your career.
Overview
Section 1: Introduction
Lecture 1 Course Overview
Lecture 2 Free copy of the study book for this course
Section 2: Module 1 - Introduction to Blockchain Foundations
Lecture 3 Overview of Blockchain Technology
Lecture 4 Key Physical Components of the Blockchain
Lecture 5 Key Logical Components of the Blockchain
Lecture 6 Linking blocks in a Blockchain: Creating the Chain
Lecture 7 Decentralization
Lecture 8 Consensus Mechanisms
Lecture 9 Data Security and Privacy
Lecture 10 Common Blockchain Layers
Lecture 11 Smart Contracts
Lecture 12 Where are Blockchains Used?
Lecture 13 Types of Blockchains
Lecture 14 Issues in Blockchain Analysis
Section 3: Module 2 Fundamentals of Cryptocurrency
Lecture 15 Understanding Cryptocurrencies
Lecture 16 What are the major Cryptocurrencies in circulation
Lecture 17 Cryptography in Blockchain and Cryptocurrencies
Lecture 18 Wallets, Addresses and Private Keys
Lecture 19 Privacy Coins
Section 4: Module 3 Blockchain Data Structures
Lecture 20 Block Formatting
Lecture 21 Transactions
Lecture 22 Understanding block format differences
Lecture 23 Merkle Trees
Lecture 24 UTXOs
Lecture 25 Smart Contracts and their role in Data Analysis
Section 5: Module 4 Analyzing Bitcoin Transactions
Lecture 26 Transaction Inputs and Outputs
Lecture 27 Transaction Scripts (OpCodes)
Lecture 28 OpCodes
Lecture 29 Blockchain Explorer Tools
Lecture 30 Tracking Transactions
Lecture 31 Etherscan.io example
Section 6: Module 5 Ethereum and Smart Contract Analysis
Lecture 32 Overview
Lecture 33 Understanding Ethereum
Lecture 34 Smart Contracts and Solidity
Lecture 35 Contract Interaction and Code Analysis
Lecture 36 Smart Contracts and Blockchain Explorers
Section 7: Module 6 Blockchain Analysis Tools
Lecture 37 Blockchain Analysis Tools
Lecture 38 Practical Use of Blockchain Tools
Lecture 39 Blockchain Analysis Platforms
Lecture 40 Wallet Reputation Scores
Lecture 41 Limitations
Lecture 42 Data Visualization
Lecture 43 Blockchain Visualization Tools
Lecture 44 Machine Learning and Data Analysis
Lecture 45 Common ML Models for Blockchain
Lecture 46 BaaS Blockchain as a Service
Lecture 47 Legal Concerns
Section 8: Visualization Hands On
Lecture 48 Gephi Part 1 Getting Started
Lecture 49 Gephi Part 2 Data Cleaning
Lecture 50 Gephi Part 3 The Social Graph
Lecture 51 Gephi Data Files Zip
Lecture 52 Bit Query
Lecture 53 Bread Crumb App
Lecture 54 Blockpath
Lecture 55 Crystal Visualization
Lecture 56 Google Big Query
Section 9: Module 7 Additional Resources
Lecture 57 Cryptocurrency Security Standard
Lecture 58 Example: Flash Loan Attacks
Lecture 59 Flash loan Example
Lecture 60 Address Clustering
Lecture 61 Responsible Disclosure
Lecture 62 Special Privacy Considerations
Lecture 63 Special Legal Considerations
Lecture 64 Data Ownership
Lecture 65 Where to find good data sources
Lecture 66 Working with Data
Lecture 67 AI/ML Using Predictive Modeling
Section 10: Final Thank you!
Lecture 68 Congratulations!
This course addresses multiple levels of knowledge about blockchain and data analysis. It is meant to be an overview of the process for chain analysis and as such is aimed more at beginners with some intermediate ideas. If you already have a certificate in blockchain data analysis or chain analysis you will probably find this course dull or repetitive in many ways. The ideal student for this course has the following traits Technical Proficiency: Students should have a strong foundation in computer science, data science, or a related technical field. Proficiency in programming languages like Python is often essential, as many blockchain data analysis tasks involve scripting and data manipulation. Blockchain Knowledge: A solid understanding of blockchain technology, its structure, and how cryptocurrencies work is crucial. Students should be familiar with key blockchain concepts like blocks, transactions, cryptographic hashing, and decentralization. Data Analysis Skills: Students should have a background in data analysis, statistics, and data visualization. They should be comfortable working with datasets, databases, and analytics tools. Curiosity and Critical Thinking: Given the complex and rapidly evolving nature of blockchain data, students should be curious and possess strong critical thinking skills. The ability to approach problems with a creative and analytical mindset is invaluable. Ethical and Legal Awareness: An understanding of the ethical and legal aspects of blockchain data analysis is important. Students should be aware of privacy concerns, consent, and regulations related to handling and analyzing blockchain data. Mathematics Proficiency: Blockchain data analysis often involves mathematical concepts, especially in cryptography and statistical analysis. Students with a background in mathematics will find it easier to grasp these aspects. Programming Skills: While not all blockchain data analysis requires extensive programming, the ability to write scripts and work with APIs is an advantage. Familiarity with libraries and tools commonly used in data analysis, like Pandas and Jupyter notebooks, can be beneficial. Patience and Attention to Detail: Blockchain data analysis can be intricate and sometimes time-consuming. Students should be patient and pay close attention to detail, as small oversights can lead to incorrect conclusions. Interest in Cryptocurrency and Blockchain: Enthusiasm for cryptocurrency and blockchain technology can be a motivating factor. A genuine interest in the subject matter often leads to more engaged learning. Adaptability: The blockchain space evolves rapidly. Students should be adaptable and willing to keep up with the latest trends, technologies, and analytical methods.
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