1CHAPTER 1 Introduction to Data Science
4912.2 Early platform examples: Ethereum, Hyperledger
21.1 Defining Data Science
5012.3 Smart Contract Programming
31.2 Evolution of Data Science
5112.4 Scalability Challenges
41.3 Data Science Process and Techniques
52CHAPTER 13 Blockchain Challenges and Limitations
51.4 Applications of Data Science
5313.1 Energy Consumption Concerns
6CHAPTER 2 Data Collection and Management
5413.2 Low Transaction Throughput
72.1 Data Sources and Formats
5513.3 Private Key Management
82.2 Data Cleaning and Preprocessing
5613.4 Regulation and Compliance
9CHAPTER 3 Exploratory Data Analysis
5713.5 Privacy and Security Issues
10Exploratory Data Analysis
5813.6 Legal and Compliance Risks
11Data Visualization
59CHAPTER 14 Careers in Data Science
12Exploratory Data Analysis
6014.1 Data Scientist
13Identifying Patterns and Outliers
6114.2 Data Engineer
14CHAPTER 4 Statistical Inference and Modeling
6214.3 Business Analyst
154.1 Probability Distributions
6314.4 Data Journalist
164.2 Statistical Hypothesis Testing
6414.5 Research Scientist
174.3 Regression Analysis
65CHAPTER 15 Careers in AI
184.4 Machine Learning Models
6615.1 AI Researcher
19CHAPTER 5 Big Data Analytics
6715.2 Machine Learning Engineer
205.1 Characteristics of Big Data
6815.3 Computer Vision Engineer
215.2 Distributed Systems and Big Data Frameworks
69CHAPTER 16 Careers in Blockchain
225.3 Real-time and Stream Analytics
7016.1 Cryptocurrency Developer
235.4 Cloud Computing and Storage
7116.2 Blockchain Engineer
24CHAPTER 6 Data Mining and Machine Learning
7216.3 Smart Contracts Developer
256.1 Supervised vs Unsupervised Learning
7316.4 Blockchain Business Strategist
266.2 Classification, Regression, Clustering
7416.5 Blockchain Legal Expert
276.3 Bias-Variance Tradeoff
7516.6 Blockchain Project Manager
286.4 Model Evaluation Metrics
76CHAPTER 17 Building a Data Science Portfolio
29CHAPTER 7 Artificial Intelligence and Neural Networks
7717.1 Personal, Academic, and Work Projects
307.1 Introduction to Artificial Intelligence
7817.2 Open Source Contributions on GitHub
317.2 Neural Network Architectures and Training
7917.3 Writing Technical Blogs and Tutorials
32CHAPTER 8 Visualization and Communication
8017.5 Presentations at Meetings and Conferences
338.1 Data Visualization Principles and Tools
81CHAPTER 18 Lifelong Learning in Technology
348.2 Interactive Visualizations and Dashboards
8218.1 Learning Emerging Tools and Techniques
358.3 Data Storytelling and Reports
8318.2 Attending Conferences and Workshops
36CHAPTER 9 Introduction to Blockchain
8418.3 Participating in Meetups and Online Forums
379.1 Decentralization Using Blockchain
8518.4 Follow Thought Leaders on Social Media
389.2 Cryptography and Consensus Mechanisms
86CHAPTER 19 Ethics in Data Science, AI, and Blockchain
399.3 Smart Contracts and DApps
8719.1 Algorithmic Bias
40CHAPTER 10 Cryptocurrencies and Financial Services: 10.1 History of Bitcoin and Early Cryptocurrencies
8819.2 Data Privacy and Re-identification Risks
41CHAPTER 11 Blockchain Use Cases
8919.3 Transparency and Explainability
4211.1 Digital identity management
9019.4 Regulatory Compliance
4311.2 Healthcare records management
9119.5 Professional Codes of Conduct
4411.3 Real estate and land registry
92CHAPTER 20 Future Outlook for Data Science, AI, and Blockchain
4511.4 Voting and governance
9320.1 Emerging Trends and Innovations
4611.5 More industry examples
9420.2 Applications to Business, Government and Science
47CHAPTER 12 Blockchain Platforms and Architecture
95Glossary
4812.1 Public vs private blockchains
