Recommended for ages 10 years old and older
Start your journey in becoming a data scientist with Python.
Python is a high-level object-oriented programming language. It is designed to be easy to understand, as it uses simple English words. It is used in game development, web development, machine learning, AI, and scientific computing. The Data Explorer 1 camp focuses on the basic concepts to develop your first calculator.
Course Outline:
- Python Environment
- Lists, Dictionaries, and Logic Formulation
- Looping
- Modules and Functions
- File Handling
- Teacher: Jet Arada
- Teacher: Marthee Batican
- Teacher: Jose Paulo Cabral
- Teacher: Joanne Kristine Costo
- Teacher: Mary Ann De Guzman
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Daniel Benedict Omoto
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
Recommended for ages 10 years old and older
Learn more about advanced concepts about data structure algorithms in Python.
Python is a high-level object-oriented programming language. It is designed to be easy to understand, as it uses simple English words. It is used in game development, web development, machine learning, AI, and scientific computing. The Data Explorer 2 camp focuses on algorithm development.
Course Outline:
- Introduction to Algorithms
- Pointers
- Stacks / Queues
- Linked Lists
- Searching and Sorting Algorithms
- Teacher: Jet Arada
- Teacher: Jose Paulo Cabral
- Teacher: Carmello Canonoy
- Teacher: Mary Ann De Guzman
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Daniel Benedict Omoto
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
Recommended for ages 10 years old and older
Python is a high-level object-oriented programming language. It is designed to be easy to understand, as it uses simple English words. It is used in game development, web development, machine learning, AI, and scientific computing. The Data Explorer 3 camp focuses on Graphic User Interface(GUI) development.
Course Outline:
- Basic Concepts of Python
- PyQT: Python GUI Designer
- PyQT: Events and Signals
- PyQT: Menu and Toolbar
- PyQT: Calculator
- Teacher: Jet Arada
- Teacher: Jose Paulo Cabral
- Teacher: Mary Ann De Guzman
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Daniel Benedict Omoto
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
Recommended for working professionals
Course Outline:
Part 1: Python Crash Course
- Python Operators
- Data Types
- Variables
- Conditional Statements
- Functions
Part 2: Linear Algebra & Numpy
- Vectors & arrays
- Vector manipulation
- Eigenvalues & Eigenvectors
Part 3: Gradient Descent
- Review of derivatives
- Curve fitting
- Gradient descent & Newton-Rhapson method
Part 4: Introduction to Pandas
- Series & Dataframes
- Reading files with Pandas
- Data frame manipulations
- Basics of data cleaning
- Teacher: Jet Arada
- Teacher: Jose Paulo Cabral
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
- Teacher: Michabelle Yap
Recommended for working professionals
Course Outline:
- Part 1: Basic Data Visualization
- Introduction to Matplotlib & Seaborn
- Elements of a good visualization
- Part 2: Basic Statistics in Python
- Part 3: Data Storytelling
- Teacher: Jose Paulo Cabral
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
- Teacher: Michabelle Yap
Recommended for working professionals
Course Outline:
- Part 1: Classification models
- Common models
- Measures of accuracy
- Part 2: Regression models
- Linear regression
- Decision trees & ensemble methods
- Time series forecasting
- Part 3: Data Mining
- Clustering
- Dimensionality reduction
- Teacher: Jose Paulo Cabral
- Teacher: Daphne Go
- Teacher: Shyrill Ogoc
- Teacher: Joseph Placiente Jr.
- Teacher: Mon Anthony Soriano
- Teacher: Michabelle Yap