Application of AI In
Computational Finance
This comprehensive program is meticulously crafted to endow participants with a robust understanding and competency in harnessing artificial intelligence (AI) and deep learning methodologies for the purpose of conducting sophisticated financial analysis, executing trading strategies, and making informed decisions within the dynamic sphere of financial markets. Delving deeply into the confluence of AI and finance, this program aims to equip learners with the ability to integrate avant-garde technological innovations for the purpose of gaining enhanced financial insights and achieving superior investment performance.
Skills & Competencies
The extensive agenda of the program is carefully designed to empower participants with the knowledge, skills, and competencies to harness the power of AI, deep learning, mathematical modeling required to solve complex problems in finance.
Methodology
This program incorporates an engaging mix of comprehensive lectures, thorough assessments, tangible practical insights, examples, and detailed case studies to equip participants with a robust mastery to harness the power of AI and deep learning in computational finance.
Learning Outcomes
Upon successful completion of this program, attendees will have achieved a high level of proficiency that enables them to:
Knowledge
1. Define and comprehend the fundamentals of computational finance.
2. Recognize the potential applications of AI and deep learning in finance.
Skills
- Apply statistical methods for data analysis and modeling.
- Build and train
deep neural networks for time series forecasting and other financial
tasks.
- Construct machine
learning algorithms for predictive financial modeling.
- Choose
appropriate evaluation metrics and perform model selection and tuning.
- Develop feature
engineering expertise for financial modeling.
Competency
- Contract AI and deep learning models to real financial problems through hands-on projects.
- Gain practical
experience in developing AI-driven financial solutions.
Duration and Mode of Delivery
The workshop extends over a period of 8 days, featuring 3 hours each day of intensive, interactive learning sessions. It is designed to be accessible and convenient for all by offering both online and in-person attendance options. Participants will be recognized with 24 PDUs (Professional Development Units) for their commitment to professional growth upon completion of the program.
Who Should Attend
This program is suitable for
individuals and professionals with varying backgrounds, including:
- Financial analysts, quants, and traders seeking to enhance their quantitative skills.
- Data scientists and machine learning engineers interested in the finance domain.
- Risk managers and professionals in financial institutions.
- Students and recent graduates aspiring to work in finance or data science.
- Professionals in the fintech industry and financial technology startups.
Profile of the Trainer
More than 20 years of teaching and research experience in Higer Education, AI, Neural Networks, and Deep Learning.
Experience in the application of Deep Learning in stock market prediction and time series.
Extensive experience in programing, statistics, data visualization, analysis, and interpretation.
Certified Lean Six Sigma Green Belt - Kansas University, USA.
- Certified AACSB Program Assessment.
- Certified AACSB Benchmarking.
- Certified ABET Fundamentals of Program Assessment.
- Reviewer of IEEE Online Learning Courses.