Course Outline
Introduction to Data Science and AI
- Acquiring knowledge through data
- Methods of knowledge representation
- Creating value from data
- Overview of Data Science
- The AI ecosystem and modern approaches to analytics
- Essential technologies
Data Science Workflow
- CRISP-DM methodology
- Data preparation processes
- Planning the model
- Building the model
- Communication strategies
- Deployment procedures
Data Science Technologies
- Languages for prototyping
- Big Data technology stacks
- End-to-end solutions for common challenges
- Fundamentals of the Python language
- Integration of Python with Spark
AI in Business
- The AI ecosystem landscape
- Ethical considerations in AI
- Strategies for implementing AI in business
Data Sources
- Different data types
- SQL versus NoSQL databases
- Data storage solutions
- Data preparation techniques
Data Analysis: Statistical Approach
- Probability concepts
- Statistical methods
- Statistical modeling
- Business applications using Python
Machine Learning in Business
- Supervised versus unsupervised learning
- Addressing forecasting challenges
- Classification problems
- Clustering problems
- Anomaly detection
- Developing recommendation engines
- Mining association patterns
- Resolving ML problems with Python
Deep Learning
- Scenarios where traditional ML algorithms fall short
- Tackling complex issues with Deep Learning
- Introduction to TensorFlow
Natural Language Processing
Data Visualization
- Presenting visual reports from modeling results
- Avoiding common visualization pitfalls
- Creating visualizations with Python
From Data to Decision: Communication
- Creating impact through data-driven storytelling
- Enhancing influence and effectiveness
- Managing Data Science projects
Requirements
No specific prerequisites or prior requirements are necessary to participate in this course.
Testimonials (7)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
Nazeera Mohamad - Ministry of Science, Technology and Innovation
Course - Introduction to Data Science and AI using Python
Trainer expertise and ability to engage students
Nikita - EY GLOBAL SERVICES (POLAND) SP Z O O
Course - Introduction to Data Science and AI using Python
Ania has great knowledge and knows how to explain even complex topics.
Kasia - EY GLOBAL SERVICES (POLAND) SP Z O O
Course - Introduction to Data Science and AI using Python
The course is very interesting being the main focus nowdays
mohamed taher - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
Ahmed was very interactive and didn’t mind answering any kind of questions Well presentation and smooth flow of the course
Mohamed Ghowaiba - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
Helpful and good listener .. interactive
Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
Subject presentation knowledge timing
