Fintech Course Concepts

1. Heuristics

1.1. Anchoring

1.2. Availability

1.3. Representativeness

2. 4 Vs of Data

2.1. Volume

2.2. Variety

2.3. Velocity

2.4. Veracity

3. Quantum Computing

4. Cognitive Biases

4.1. Bandwagon

4.2. Choice Supportive

4.3. Confirmation Bias

4.4. Placebo

4.5. Overconfidence

4.6. Survivorship

4.7. Selective

4.8. Blindspot

4.9. Ostrich Bias

5. Nudge Theory

6. Regulatory Sandbox

7. Data Platforms

7.1. PowerBI

7.2. Alteryx

7.3. Tableau

8. SAS

8.1. Tidy Data

8.2. Feature Engineering

8.3. Importing Data

8.4. Merging

8.5. Accumulating

8.6. Panel Data

8.7. Visualization

9. AI Biases

9.1. Interaction Bias

9.2. Latent Bias

9.3. Selection Bias

10. Data Integrity

10.1. Validity

10.2. Completeness

10.3. Accuracy

10.4. Consistency

10.5. Uniformity

11. Limitations on Data

11.1. Garbage-In-Garbage-Out

11.2. Spurious Correlations

11.3. Data Labeling

12. Learning

12.1. Artificial Intelligence

12.2. Supervised

12.3. Unsupervised

12.4. Machine Learning

12.5. Deep Learning

13. Internet of Things

14. Big Data

14.1. Structured

14.2. Unstructured

15. BlockChain

16. Data Analytics

16.1. Descriptive

16.2. Predictive

16.3. Diagnostic

16.4. Prescriptive

17. Alternative Data

17.1. Web scraping

17.2. Sentiment Analysis