Concise and hands-on, this carefully selected curriculum will ensure you are equipped to solve real-world business problems in just five days. While the focus is on practical skills, there will be sufficient coverage of data science theory as well.
- Bootcamp Preparation: Python Crash Course Webinar (One Week before Bootcamp)
- Fundamentals of Data Science: Data Quality, Models, Metrics, Question Everything!
- Cloud computing: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform
- Machine Learning (ML) Fundamentals: Frequently Used Models and Algorithms
- Regression Models: Linear Regression
- Unsupervised Learning: K-means Clustering
- Ensemble Methods: Bootstrapping and Bagging
- Operationalize ML Models: Cloud Deployment
- Low Code environments: Build and Deploy Data Science Models Rapidly
- Advanced Topics: Model Explainability, Data Drift, Automated Machine Learning
- Challenges of Prediction: Biases, Paradoxes, Critical Reasoning, Data Snooping
- Domain Specific Modelling: Genetic Algorithms
- Generative Artificial Intelligence (Gen AI)- Chat GPT, Dall-E, etc.
- Data Engineering: Create an End-to-End Big Data pipeline.
- Introduction to Deep Learning: Convolutional Neural Networks
- Tableau and Wolfram Mathematica: The Data Scientist’s Extended Tool Box
- Practitioner’s Guide: Common Pitfalls, Tips, Tricks, Best Practices - Based on My Mistakes!
Reskill in the age of Artificial Intelligence!