Course Outline
Introduction to Data Science and AI
- Gaining insights through data
- Methods of knowledge representation
- Generating value from data
- Overview of Data Science
- The AI ecosystem and modern approaches to analytics
- Essential technologies
Data Science Process
- The CRISP-DM framework
- Preparing data
- Planning the model
- Constructing the model
- Communicating results
- Implementation and deployment
Technologies in Data Science
- Languages for prototyping
- Big Data infrastructure
- Comprehensive solutions for common challenges
- Fundamentals of the Python language
- Integrating Python with Spark
AI in Business
- The AI landscape
- Ethical considerations in AI
- Strategies for integrating AI into business operations
Data Sources
- Categorizing data types
- SQL versus NoSQL databases
- Data storage mechanisms
- Data preprocessing
Data Analysis: A Statistical Perspective
- Concepts of probability
- Statistical principles
- Statistical modeling techniques
- Practical business applications using Python
Machine Learning in Business
- Supervised versus unsupervised learning
- Predictive forecasting
- Classification tasks
- Clustering techniques
- Identifying anomalies
- Building recommendation systems
- Mining association patterns
- Addressing ML challenges with Python
Deep Learning
- Limitations of traditional ML algorithms
- Tackling complex issues with Deep Learning
- Getting started with TensorFlow
Natural Language Processing
Data Visualization
- Presentation of modeling outcomes
- Common errors in visualization
- Creating visualizations with Python
From Data to Decision-Making: Communication
- Creating impact through data-driven narratives
- Enhancing the effectiveness of influence
- Overseeing Data Science projects
Requirements
No prior specific requirements are necessary 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
