Fintech For Finance Professionals
- Length: 295 pages
- Edition: 1
- Language: English
- Publisher: WSPC/OTHERS
- Publication Date: 2021-12-02
- ISBN-10: 9811241864
- ISBN-13: 9789811241864
- Sales Rank: #4791129 (See Top 100 Books)
As technologies such as artificial intelligence, big data, cloud computing, and blockchain have been applied to various areas in finance, there is an increasing demand for finance professionals with the skills and knowledge related to fintech. Knowledge of the technologies involved and finance concepts is crucial for the finance professional to understand the architecture of technologies as well as how they can be applied to solve various aspects of finance. This book covers the main concepts and theories of the technologies in fintech which consist of big data, data science, artificial intelligence, data structure and algorithm, computer network, network security, and Python programming. Fintech for Finance Professionals is a companion volume to the book on finance that covers the fundamental concepts in the field. Together, these two books form the foundation for a good understanding of finance and fintech applications which will be covered in subsequent volumes.
Cover Page Title Page Copyright Page Preface About the Editors Contents Part I: Data Structures Chapter 1 Python Programming Basics 1.1 Introduction 1.2 Python Programming References/Further Readings 1.3 Sample Questions Solutions Chapter 2 Data Structure and Algorithms 2.1 Introduction to Data Structure and Algorithms 2.2 Abstract Data Types 2.3 Arrays and Lists 2.4 Stacks and Queues 2.5 Searching and Sorting References/Further Readings 2.6 Sample Questions Solutions Part II: Big Data and Data Science Chapter 3 Big Data 3.1 Introduction 3.2 Characteristics of Big Data 3.3 Big Data Architecture 3.4 Big Data Technologies 3.5 Big Data Applications 3.6 Advantages and Disadvantages of Big Data 3.7 Trends and Challenges of Big Data References/Further Readings 3.8 Sample Questions Solutions Chapter 4 Data Science 4.1 Introduction 4.2 Data Science Pipeline 4.3 Trends and Challenges 4.4 Comparison: Big Data vs. Data Science References/Further Readings 4.5 Sample Questions Solutions Part III: Artificial Intelligence and Machine Learning Chapter 5 Artificial Intelligence 5.1 Introduction of Artificial Intelligence References/Further Readings 5.2 Sample Questions Solutions Chapter 6 Machine Learning 6.1 Applied Math and Machine Learning Basics 6.2 Unsupervised Machine Learning 6.3 Supervised Machine Learning References/Further Readings 6.4 Sample Questions Solutions Chapter 7 Deep Learning 7.1 Introduction of Deep Learning References/Further Readings 7.2 Sample Questions Solutions Part IV: Computer Network and Network Security Chapter 8 Computer Network 8.1 Introduction 8.2 Five Layers References/Further Readings 8.3 Sample Questions Solutions Chapter 9 Network Security 9.1 Introduction 9.2 Web Security References/Further Readings 9.3 Sample Questions Solutions
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