Data science is a skill in demand in this modern age with buzzwords like big data, artificial intelligence, machine learning, deep learning etc.
In this video recording of our comprehensive 3-day online course, you will be learning 3 important skills to becoming a data scientist.
Python is so popular because it is easy to read, understand and use. This makes it a great place to start for people new to programming. With basic python, you can then move on to use the powerful data science packages available.
Go through basic statistics, then move on to use Pandas, a Python library, to prepare your data for analysis. Communicate insights by creating diagrams and charts that describe large amounts of data but are easy to understand.
Next, learn about supervised and unsupervised machine learning. Use machine learning, Python libraries again, to go through data and try to predict future values or extract insights. Next, try different libraries to see which does predictions best.
✓ Acquire basic mathematical and statistical knowledge
✓ Set up your Python coding environment
✓ Evaluate and pre-process data
✓ Access data sets e.g. financial, digital marketing
✓ Perform data mining using Pandas
✓ Perform data visualization using Matplotlib
✓ Perform machine learning using scikit, Tensorflow, Keras
Course Accreditation
This course is accreditated under the Singapore Workforce Skills Qualification system.
The Singapore Workforce Skills Qualifications (WSQ) is a national credential system that trains, develops, assesses and certifies skills and competencies for the workforce.
WSQ training programmes are based on skills and competencies validated by employers, unions and professional bodies, ensuring existing and emerging skills and competencies in demand are used to inform training and development.
Leader in data science and digital transformation with more than 20 years of experience in team setup and strategic business insights leading to data-driven results for Asia Pacific and global markets.
Data Science coverage: Predictive Modelling, Machine Learning, Deep Learning, Blockchain, Computer Vision, Natural Language Processing, Digital Music, Knowledge Graph, Multi-agent Systems, Internet-of-Things (IoT).
Industry experiences: Banking, eCommerce, B2B, Retail, Distribution, Media & Advertising, IT, Aerospace.