Target audiences
- Financial analysts using data analytics
- Data scientists in finance
- Investment researchers focusing on data analysis
- Quantitative analysts using big data
- Professionals handling financial data analytics
The Financial Analytics and Big Data training program is designed to equip participants with the skills and tools needed to analyze large and complex financial datasets using modern data analytics techniques. The program covers key topics such as data mining, machine learning, predictive analytics, and data visualization, as well as their applications in finance. Participants will also learn about the latest tools and technologies used in big data analytics and their applications in the financial industry.
Objectives:
- Develop a comprehensive understanding of financial analytics and big data concepts
- Learn how to collect, clean, and transform large and complex financial datasets
- Understand how to use data mining and machine learning techniques to uncover hidden patterns and relationships in financial data
- Learn how to use predictive analytics to make informed financial decisions
- Understand the principles of data visualization and how to communicate insights effectively
- Learn about the latest tools and technologies used in big data analytics and their applications in finance
Overall, this Financial Analytics and Big Data training program is suitable for financial analysts, data analysts, business analysts, and anyone involved in financial decision-making or data analysis. The program provides a deep dive into the principles of financial analytics and big data, and equips participants with the tools and techniques needed to analyze large and complex financial datasets and make informed decisions. The program is highly interactive, with case studies and exercises to help participants apply their learning in real-world situations.
Day 1:
- Introduction to financial analytics and big data
- Overview of data analytics techniques and their applications in finance
- Collecting, cleaning, and transforming financial data
- Introduction to Python programming for data analytics
Day 2:
- Data mining and machine learning for financial data analysis
- Understanding supervised and unsupervised learning
- Feature selection and engineering
- Building and evaluating machine learning models for financial data
Day 3:
- Predictive analytics for financial decision-making
- Understanding time series forecasting
- Building and evaluating predictive models for financial data
- Introduction to reinforcement learning
Day 4:
- Data visualization and communication
- Principles of data visualization and effective communication of insights
- Using Tableau for financial data visualization
- Designing dashboards and reports for financial decision-making
Day 5:
- Big data tools and technologies for finance
- Overview of Hadoop, Spark, and other big data tools and technologies
- Applications of big data in finance
- Case study: Using big data analytics to inform investment decisions
All our courses are provided in business centers located close to the city center.
After your course registration is complete, you will receive the invoice and comprehensive course details, which encompass information about the venue, instructor, classroom location and various logistical aspects.
For more details please contact us here