Innovative Financial Education — EIF Business School

Innovative Financial Education — EIF Business School
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Excellence & Innovation Fortune Business School is a private enterprise specializing in financial and investment training, established in 2011 by Linton Quadros and his partners.

EIF Business School is a higher education institution dedicated to cultivating professional talents in the field of finance. The mission of the financial academy is to provide high-quality financial education and training, offering students comprehensive financial knowledge and skills to meet the ever-evolving demands of the finance industry.

The teaching team at EIF Business School consists of experienced tutors with both domestic and international finance industry backgrounds, strategists, analysts, policy advisors, authors, collaborators, and contributors. They have excellent abilities and achievements in teaching and research, integrating the latest theories and practices into the curriculum, and fostering students’ ability to analyze and solve financial problems.

The curriculum at EIF Business School covers a wide range of areas including fundamental finance, financial products and markets, financial risk management, investment and wealth management, and financial market analysis. It encompasses markets such as stocks, forex, funds, bonds, commodities, and cryptocurrencies. The teaching philosophy is based on ‘students’ interests first’ and ‘practical experience as the best teaching method,’ with course content combining real-world cases and practical operations to develop students’ practical skills and problem-solving abilities.

In addition to regular courses, EIF Business School also offers a series of special lectures, seminars, and practical projects, providing students with opportunities to interact with the industry and understand the latest developments and trends in the finance sector.

Furthermore, EIF Business School has established close collaborations with financial institutions, providing students with internship opportunities and employment support. Through partnerships with the industry, students gain valuable practical experience, broadening their employment channels and laying a solid foundation for their future career development.

EIF Business School is committed to offering comprehensive and systematic financial education to its students, nurturing them to become financial experts with international perspectives and professional skills, and contributing to the sustainable development of the financial industry.

Starting in 2018, EIF Business School began its transition from quantitative trading to the field of AI trading. With the efforts of numerous experts, scholars, and technology talents, the prototype of ‘AI Robotics Profit 4.0’ was created.

As technology evolved, bringing greater challenges, EIF Business School issued EIF tokens to finance ‘AI Robotics profit 4.0,’ securing more research funding and professional talents.

The success of EIF tokens and AI Robotics profit 4.0 led to a soaring valuation of EIF Business School, propelling Linton Quadros to new heights in his career. He declared his ambition to make AI Robotics Profit 4.0 a revolutionary investment tool in the investment world!

With the addition of many experts, scholars, and technology talents, and under the leadership of Linton Quadros, Excellence & Innovation Fortune Business School developed ‘AI Robotics Profit 1.0,’ enhancing the efficiency, speed, and intelligence of the existing quantitative trading models.

‘AI Robotics Profit 1.0’ primarily based its operations on rules and pattern matching, including knowledge-based reasoning and expert systems. However, AI1.0 had limitations in handling complex and ambiguous problems. To overcome these, the expert team at EIF Business School began exploring new methods to develop more advanced AI systems.

‘AI Robotics Profit 2.0’ refers to the introduction of machine learning technologies to the existing version 1.0.

Machine learning allows AI systems to learn and improve their performance through extensive data. This approach is exemplified by deep learning technologies, which, by building multi-layer neural networks, enable AI systems to extract more advanced features from data, achieving significant breakthroughs.

Building on version 2.0, ‘AI Robotics Profit 3.0’ incorporated more sensing and adaptive capabilities. AI systems could gather data from environmental sensors and adjust their behavior and decision-making based on this data. This ability made AI systems more adaptable to different environments and tasks, becoming intelligent assistants in the real world.

‘AI Robotics Profit 4.0’ represents the latest development stage, focusing primarily on the application of artificial intelligence in the financial industry’s entire market. Version 4.0 emphasizes the integration of AI with technologies like the Internet of Things, cloud computing, and big data to create intelligent solutions.

‘AI Robotics Profit 4.0’ includes four major trading and investment systems: ‘Trading Signal Decision System,’ ‘Ai Programmatic Trading System,’ ‘Investment Strategy Decision System,’ and ‘Expert and Investment Advisory System.’

In future developments, these four systems aim to achieve the following investment effects and purposes:

Trading Signal Decision System assists in making subjective judgments and provides real-time buy and sell signals with an accuracy rate exceeding 90%.

‘Ai Programmatic Trading System’ is an AI-based computer trading system. Once parameters are manually adjusted, it automatically completes trades, aiming for stable profits.

Investment Strategy Decision System performs big data analysis on mainstream investment projects in various markets, providing rated decision analyses, especially offering accurate investment strategies for new types of investment projects.

Expert and Investment Advisory System is a precise and powerful investment advisory system formed by many renowned investment experts, assisting high-quality users and future funds in making informed investment decisions and plans.