Deep Learning in Finance with R

Benefits

• Upon completion of the training, the participant will be able to design and implement advanced Deep Learning models for financial applications in R
• The ability to effectively train deep neural networks on financial data
• How to select appropriate network architectures for specific financial problems
• Will be able to optimize the performance of Deep Learning models in a production environment
• Will learn methods for interpreting and validating Deep Learning models in a financial context
• Will gain the ability to implement Deep Learning solutions in financial systems
• Will master techniques for monitoring and maintaining models in a production environment.Upon completion of the training, the participant will be able to effectively manage Big Data initiatives within the organization
• He or she will gain the ability to create and implement a data-driven digital transformation strategy
• He or she will learn to assess the maturity of the organization in terms of Big Data usage
• Will be able to build and develop analytics teams
• Will learn methods to effectively manage change in Big Data projects
• Will gain the ability to measure and communicate the business value of analytics initiatives
• Will master risk management techniques for projects using Big Data.Upon completion of the training, the participant will be able to use advanced Business Intelligence tools in forensic analysis
• He or she will gain the ability to integrate diverse data sources into the investigative process
• To identify crime patterns using analytical techniques
• Will be able to create advanced visualizations of criminal links
• Will learn methods of predictive crime analysis
• Will gain the ability to effectively document the analytical process according to standards
• Will master techniques for securing and presenting electronic evidence.Upon completion of the training, the participant will be able to design and implement solutions using the Vespa platform
• He or she will gain the ability to create efficient applications that process data in real time
• To optimize the performance and scalability of Vespa-based systems
• Will be able to integrate Vespa with existing systems and tools
• Will learn techniques for effective application monitoring and maintenance
• Will gain the ability to solve performance problems in large-scale systems
• Will master methods for deploying and managing applications in a production environment.Upon completion of the training, the participant will be able to design and implement advanced Data Science solutions in a Big Data environment
• He or she will gain the ability to create scalable analytical models adapted to large data sets
• To select and implement appropriate machine learning algorithms for specific use cases
• Will be able to optimize model performance in a production environment
• Will learn techniques for effective lifecycle management of analytical models
• Will gain the ability to integrate Data Science solutions with existing Big Data infrastructure
• Will master methods for monitoring and updating models in real time