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Course Outline
Introduction to AI in the Financial Sector
- Overview of AI applications in finance (fraud detection, algorithmic trading, risk assessment)
- Introduction to data analysis principles and types of financial data
- Ethical considerations and regulatory compliance in AI implementation
- Setting up Python/R environment for financial data analysis
Data Collection and Preprocessing
- Data sources in the financial sector (stock data, market indices, customer data)
- Data cleaning, normalization, and transformation techniques
- Feature engineering for enhanced data analysis
- Preprocessing a financial dataset for analysis
Machine Learning Algorithms for Financial Data
- Supervised learning algorithms (linear regression, decision trees, random forest)
- Unsupervised learning for anomaly detection (k-means clustering, DBSCAN)
- Case study analysis: Credit scoring models and risk management
- Building a supervised model for predicting stock prices
Advanced AI Techniques and Model Optimization
- Deep learning models for financial data (LSTM for time-series forecasting)
- Introduction to reinforcement learning for decision-making in trading strategies
- Hyperparameter tuning and model validation
- Implementing LSTM for financial time-series data
Visualization, Interpretation, and Reporting
- Data visualization best practices using libraries (Matplotlib, Seaborn, Tableau)
- Interpreting model outputs for business insights
- Creating comprehensive reports for stakeholders
- Analyze and present financial data using a complete AI workflow
Summary and Next Steps
Requirements
- Basic knowledge of Python/R programming
- Understanding of financial terminology and basic statistics
Audience
- Financial analysts
- Data scientists
- Risk managers
28 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £7600 online delivery, based on a group of 2 delegates, £2400 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
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Testimonials (4)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
Share example of application
Course - Alteryx for Data Analysis
Very clearly articulated and explained
Harshit Arora - PwC South East Asia Consulting
Course - Alteryx for Developers
Linear regression - the algorithm to predict the trend
