Course Outline
Introduction to Data Science/AI
- Acquiring knowledge through data
- Representing knowledge in computational models
- Creating value from information
- Overview of Data Science concepts
- The AI ecosystem and modern analytics approaches
- Essential technologies
Data Science workflow
- Crisp-dm framework
- Preparing data for analysis
- Planning the model strategy
- Building machine learning models
- Communicating insights
- Deploying solutions
Data Science technologies
- Programming languages for rapid prototyping
- Big Data technologies
- End-to-end solutions for common challenges
- Foundations of the Python language
- Integrating Python with Spark
AI in Business
- Understanding the AI ecosystem
- Ethical considerations in AI
- Strategies for driving AI adoption in business
Data sources
- Different types of data
- SQL versus NoSQL databases
- Data Storage mechanisms
- Data preparation techniques
Data Analysis – Statistical approach
- Probability theory
- Statistical methods
- Statistical modeling
- Business applications using Python
Machine learning in business
- Supervised versus unsupervised learning
- Forecasting challenges
- Classification challenges
- Clustering challenges
- Detecting anomalies
- Developing recommendation engines
- Mining association patterns
- Addressing ML problems using Python
Deep learning
- Scenarios where traditional ML algorithms fall short
- Tackling complex problems with Deep Learning
- Getting started with Tensorflow
Natural Language processing
Data visualization
- Presenting visual reporting outcomes from models
- Avoiding common visualization pitfalls
- Creating visualizations with Python
From Data to Decision – communication
- Making an impact: data-driven storytelling
- Enhancing influence and effectiveness
- Managing Data Science projects
Requirements
Participants do not need to meet any specific prior requirements to enroll 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
