Data Science and Machine Learning Basic in January

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Hi all members.

We will have a new Data Science and Machine Learning course in Jan 2019. This will be continuation of Python basic course. The course will be divided into 2, basic and advance.

SkillsFuture funding has been approved, you can book your seat here.

This is a face to face class, with additional self-learning practice on Solace Tech’s e-learning platform here in between the sessions, spread for 6 days before the class and the second face to face session. Participants expected to run through the e-learning portal before the course for the participants’ benefit, since usually for complete beginners it is harder to grasp the concept without repetitions.

Here is the learning flow of the course:
1. Participants spend 3 hours self-learning one week before the course, spread in 6 days, to read materials and do exercises, 7 days before the course. The goal is to get familiar with some materials that are not straightforward and need repetition to understand.
2. The first face to face session, participants will learn with instructor guidance for 7.5 hours. In this session, participants expected to have questions from self-learning session, and the instructor will help to connect the dots
3. Another one week period to be spent for self-learning, where participants expected to spend 3 hours to do exercise and to submit the exercises to be evaluated by Solace Tech’s team, to assess participants’ understanding of the first session.
4. The second face to face session, participants will do a project guided by the instructor.

After this course, participants should be able to :
•acquire data by consuming an API
•use standard tools in data science project (Conda, Miniconda, Jupyter)
•Store and analyze data in a relational database, load the data from a database into python for analysis
•clean and transform data
•Familiar with standard libraries used in data science project (Numpy, Pandas, scikit-learn)
•Understand the basic concept of data visualization and standard charts (barplot, histogram, line chart, boxplot, scatterplot)
•Understand how a data science project end to end with basic linear modeling
•Understand all the activities to be done in a typical data science project
•compete on Kaggle to get recognized within a data science community

The course will be a hands-on approach where participants will be expected to write code. Participants will receive e-certificate at the end of the course to mark the completion of the course.

This course is also the pre-requisite course to join advance data science course here.

Maximum 10 participants per class. The venue would be at Depot Road.

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is canceled, we will refund 100% to you.

Note that the minimal class size to start a class is 3.