Junior Data Analyst
About the Programme
The Junior Data Analyst programme is developed by Nullspace as part of the Computer Enrichment Programme (CEP) for Gifted Education Programme (GEP) schools.
We use the popular Python 3.0 to teach contemporary and industry relevant skillsets such as data processing, machine learning, and computer vision for self-driving robot cars.
There is a total of 60 hours of hands-on coursework spread over 6 levels.
What Will Students Receive?
Digital and Physical Certificate of Completion
Certificate will be issued upon passing of the respective Python Proficiency Test
To register, visit our sign-up page.
C4RL-WEST (Rochester Mall) & C4RL-EAST (Siglap). [Centre Information]
We have both weekly weekend classes and school holiday classes. Scroll below for the updated schedule.
Python Coding Class Activities
The easy way to learn computing skills!
There are 6 levels in the program. Each level consists of 4 sessions x 2.5 hours of course work. Students will be working on their project individually (no sharing of laptops). Laptops will be provided for use in this programme.
Introduction to Python
Introduction to programming & Python syntax
- Navigating through Python IDE programming interface
- Learn to write simple Python scripts and basic troubleshooting
Using variables & operators
- Understand common data types used and solving arithmetic problems
- Learn to include various conditionals into Python scripts
- Using various loops to perform selective repetition and sequence iterations
Big Data & File Processing
Data types & formatting
- Format data sequences to optimize display outputs
File operations & processing
- Read and write external text files for data cleaning and modifications
Object oriented programming
- Understand Class objects and attributes
Classes & methods
- Use of special class methods and operator overloading
Objects & Python GUI
- Working with multiple classes with inherited attributes and methods
Introduction to Python Graphical User Interface (GUI)
- Learn to generate external Python GUI window and its settings
- Understand basic widgets to be added to interact with users
Widget organisations on GUI
- Understand advanced widgets that accepts user inputs
- Mixing widgets together to create interactive GUI windows
Data Analytics and Exploration
Introduction to NumPy
- Work with data arrays and manipulation
- Data visualization through charts and graphs to observe trends
Data analysis with pandas
- Clean and process data from CSV format data files
Data exploration with seaborn
- Advanced data visualization with multi-variable comparisons
Introduction to Machine Learning
Basic machine learning algorithms
- Understand simple prediction and categorizing algorithms
- Learn to assess and evaluate machine learning algorithms for comparisons
Introduction to deep learning
- Understand basic structure of neural networks and their components
Simple neural networks
- Create sequential models for datasets and perform training and testing of data
Deep Learning with Images
Convolutional neural network
- Work with special layer types and understanding their effects
Introduction to image recognition
- Understand how images are processed and converted for recognition
- Create sequential models for simple image datasets to test accuracy
Image pre-processing for custom datasets
- Look into pre-processing steps for file organization of custom datasets
- Preparing custom training and testing datasets in directories
Raspberry Pi & Python GUI
Computer Vision & Self Driving Robot Cars
Python Coding Class Schedule (2021)
Register for our weekend or school holiday programmes today!
Our year end holiday programmes will be offered on a home based learning format through online video conferencing. Maximum of 3 students per instructor to allow for more personalised instruction and guidance.
If you are intending to register for just one course level (4 sessions x 2.5 hours @ $380), you may proceed to register and make payment without purchasing course package.
Registration of the class is only confirmed upon payment of course fees (via credit card / PayPal) upon checkout, or by redeeming an existing course package.