Introduction to Data Science and AI using Python Training Course

Introduction to Data Science/AI

• Knowledge acquisition through data
• Knowledge representation
• Value creation
• Data Science overview
• AI ecosystem and new approach to analytics
• Key technologies

Data Science workflow

• Crisp-dm
• Data preparation
• Model planning
• Model building
• Communication
• Deployment

Data Science technologies

• Languages used for prototyping
• Big Data technologies
• End to end solutions to common problems
• Introduction to Python language
• Integrating Python with Spark

AI in Business

• AI ecosystem
• Ethics of AI
• How to drive AI in business

Data sources

• Types of data
• SQL vs NoSQL
• Data Storage
• Data preparation

Data Analysis – Statistical approach

• Probability
• Statistics
• Statistical modeling
• Applications in business using Python

Machine learning in business

• Supervised vs unsupervised
• Forecasting problems
• Classfication problems
• Clustering problems
• Anomaly detection
• Recommendation engines
• Association pattern mining
• Solving ML problems with Python language

Deep learning

• Problems where traditional ML algorithms fails
• Solving complicated problems with Deep Learning
• Introduction to Tensorflow

Natural Language processing

Data visualization

• Visual reporting outcomes from modeling
• Common pitfalls in visualization
• Data visualization with Python

From Data to Decision – communication

• Making impact: data driven story telling
• Influence effectivnes
• Managing Data Science projects