Technology

Science and Nature

Data Science, AI, and Blockchain

By Ekaaksh Deshpande

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Length5h 26m

About this audiobook

"Data Science, AI, and Blockchain: Integrated Approaches" emerges as a beacon for undergraduate students navigating the intricate landscapes of these transformative technologies. Our primary objective is to empower students with a comprehensive understanding of the synergy between Data Science, Artificial Intelligence (AI), and Blockchain, recognizing them as pivotal forces propelling innovation across diverse industries. We begin with Data Science, centered on extracting knowledge and insights from vast datasets, navigating through fundamental principles, methodologies, and tools. Real-world applications illustrate the significance of data-driven decision-making. Seamlessly moving into Artificial Intelligence, the book demystifies the algorithms underpinning intelligent systems. By weaving together theoretical concepts with practical examples, students gain insights into machine learning, natural language processing, and computer vision. Ethical considerations accompany the exploration, urging students to contemplate societal impacts. The exploration culminates in Blockchain, a revolutionary technology disrupting traditional notions of trust and transparency. Students understand how Blockchain secures transactions, empowers smart contracts, and transforms industries. Practical insights into building decentralized applications (DApps) are provided. Interactive elements, case studies, and exercises engage students actively. By fostering a multidisciplinary approach, we aim to equip undergraduates with the knowledge and skills needed to thrive in a world where the convergence of Data Science, AI, and Blockchain is reshaping the future.

Artificial Intelligence Futuristic Exploration

Audiobook details

GenreTechnology, Science and Nature

Length5 hrs 26 mins

Narrated byListen with 1,000+ voices

FormateBook with Audio

Publish dateFeb 20, 2025

LanguageEnglish

1CHAPTER 1 Introduction to Data Science

21.1 Defining Data Science

31.2 Evolution of Data Science

41.3 Data Science Process and Techniques

51.4 Applications of Data Science

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6CHAPTER 2 Data Collection and Management

72.1 Data Sources and Formats

82.2 Data Cleaning and Preprocessing

9CHAPTER 3 Exploratory Data Analysis

10Exploratory Data Analysis

11Data Visualization

12Exploratory Data Analysis

13Identifying Patterns and Outliers

14CHAPTER 4 Statistical Inference and Modeling

154.1 Probability Distributions

164.2 Statistical Hypothesis Testing

174.3 Regression Analysis

184.4 Machine Learning Models

19CHAPTER 5 Big Data Analytics

205.1 Characteristics of Big Data

215.2 Distributed Systems and Big Data Frameworks

225.3 Real-time and Stream Analytics

235.4 Cloud Computing and Storage

24CHAPTER 6 Data Mining and Machine Learning

256.1 Supervised vs Unsupervised Learning

266.2 Classification, Regression, Clustering

276.3 Bias-Variance Tradeoff

286.4 Model Evaluation Metrics

29CHAPTER 7 Artificial Intelligence and Neural Networks

307.1 Introduction to Artificial Intelligence

317.2 Neural Network Architectures and Training

32CHAPTER 8 Visualization and Communication

338.1 Data Visualization Principles and Tools

348.2 Interactive Visualizations and Dashboards

358.3 Data Storytelling and Reports

36CHAPTER 9 Introduction to Blockchain

379.1 Decentralization Using Blockchain

389.2 Cryptography and Consensus Mechanisms

399.3 Smart Contracts and DApps

40CHAPTER 10 Cryptocurrencies and Financial Services: 10.1 History of Bitcoin and Early Cryptocurrencies

41CHAPTER 11 Blockchain Use Cases

4211.1 Digital identity management

4311.2 Healthcare records management

4411.3 Real estate and land registry

4511.4 Voting and governance

4611.5 More industry examples

47CHAPTER 12 Blockchain Platforms and Architecture

4812.1 Public vs private blockchains

4912.2 Early platform examples: Ethereum, Hyperledger

5012.3 Smart Contract Programming

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