In Applied Data Science, you’ll gain a solid understanding of the mathematical machinery behind the cool algorithms, enabling you to predict future events using data.
Being hands-on is huge at Forward School. So, to make your experience more practical, you’ll learn all the essential concepts through real-world examples and applied learning projects.
After mastering them, you’ll be ready to raw, messy data into actionable business insights– or impress the other side of the table in job interviews. Our graduates are putting their skills to work in areas as diverse as medicine, manufacturing, business, and education.
- Able to build and deploy your first Django Web Application
- Able to perform data scraping and apply natural language processing to text data
- Able to implement regression and classification methods, as well to understand concepts including, overfitting, underfitting, bias, optimization, regularization and parameter tuning
- Able to understand the inner working concepts of various machine learning models, train, validate and test models and evaluate said models for accuracy metrics.
Week 1-3: Data Scraping and Web Application Development
This module covers data scraping techniques and basic web application development using Python Django. At the end of this module, students will be comfortable scraping text, numbers, social and image data from variety of sources off the Internet and perform analysis and visualizations on them. Students will also be taught how to develop their first CRUD Django web application and build their data dashboard.
- Writing and running Python scripts for data scraping and analysis
- Learn to create and deploy Django-powered web app with interactive pivot tables and charts.
- Learn how to navigate through projects and edit scripts using the command line.
- Learn about and use Git to make changes to projects.
Mini Project 2: Data Scraping, Django Web App and Visualization
Week 4-6: Supervised and Unsupervised Learning
This module will cover the common machine learning algorithms that all data scientists must be familiar with when taking on an industry role. Students will be taught to dissect the mathematics behind some standard machine learning models, train, validate and test their models and evaluate their models for accuracy.
- Text Mining and NLP Techniques
- Decision Trees & Random Forests.
- Bagging and Boosting
- Principal Component Analysis and Functional Discrimination Analysis
- Dimension Reduction
- Naïve Bayes
- Model Evaluation Metrics.
Week 7-9: Deep Learning, Big Data, Cloud Computing
This module will introduce more advanced concepts such as Deep Learning, Big Data and Cloud Computing technologies. Students will be taught how to design and implement "artificial neural network” learns and make intelligent decisions on its own, tools and technologies to handle Big Data as well as Cloud Computing terminologies and concepts.
- Introduction to Deep Learning
- Introduction to Deep Learning
- Introduction to Neural Network and Keras framework
- Introduction to Big Data and Hadoop framework
- Cloud Computing Overview
- Data Science for Image Processing and Computer Vision
Mini Project 3: Shopping Recommendation Engine
- Full Tuition Fee: RM 8,400
- HRDF Claimable
- Scholarships available
Hands-on, in-person training at our flagship campus. Low learner to instructor ratios enable personalized instruction for a premium learning experience.
Premium, Instructor-led online digital skills training – from anywhere in the world. Small class sizes encourage engagement and provide an unmatched learning experience.