WHAT IS DS102?
Data science and analytics are the current hot topics in both academia and industry. This course aims to introduce data science and analytics to students with no relevant background. Through this course, students will learn the types of problems that can be solved by data science and analytics.
The students will also be introduced to the three broad topics in data science and analytics: data management, data visualization and machine learning techniques. Learning in this course will be very “hands-on” and classes are designed to allow students to practise the techniques and concepts discussed in the lectures.
DS102 is the 2nd series of our data science track and is not meant for beginners to python programming. Beginners to Python can join our DS101 course instead.
JOB OPPORTUNITIES
Data Science is the fastest-growing job and was voted as the #1 job of 2018
HIGH PAYING CAREERS
Data Scientists earn an estimated mid-career salary of $104,000 annually
BIG DATA ANALYTICS
Demand for Big Data jobs are expected to increase exponentially in the future
An exceptionally unique experience tailored to you.
Awesome Student Welfare
Great wholesome food provided during each lesson so that students are in the best state of mind to learn.
Highly Interactive Course
Learn in a class where we integrate engaging class participation activities such as games to facilitate learning.
Industry Relevant Projects
Learn how to create insights from real data through the YouTube, Lazada and Airbnb projects within the course.
DATA SCIENCE TRACK
DATA SCIENCE 101
Build your foundations in the tools-of-the-trade (python) over 7 weeks.
DATA SCIENCE 102
Learn to perform data exploration, visualisation, and machine learning using advanced python libraries.
DATA SCIENCE 103
Learn to build an enterprise level end-to-end data analytics model with a data pipeline.
The Data Science 101 (DS101) course is built for beginners with no background in programming. Finishing DS101 prepares students for the Data Science 102 (DS102) course, where they learn about data analytics toolsets in Python. DS102 can also be taken by software engineers who are already well versed in Python. In our master class, Data Science 103, students will graduate with data know-how in an organisation setting and be certified as a data analyst by our academy.
DS102 Course Details
DS102 will be held once a week over 7 consecutive weeks. Each session would be 3 hours long held at 991D Alexandra Road #01-22/23 Singapore 119972. The course fees is $2000 before subsidy however Singaporeans and PRs are eligible for subsidies of up to 100%.
This course is an advance Python course and trainees are required to have the prerequisites before commencing the course. These prerequisites are also covered in our DS101 series.
Prerequisite
DS102 is our advance course after DS101 and hence all students are already expected to have a good working knowledge of Python programming. If you find that you do not have these competencies, consider taking the DS101 course instead.
Basic python syntax and data structure
Familiar with python syntax, and the data structure (list, dictionaries, tuples)
Python Conditions and Iterations
Familiar with if, elif and else conditional constructs, as well as writing iterations using python for and while loops
Functions and Libaries
Know how to write python functions, read python library documentations and make use of python libraries
COURSE CURRICULUM
Find out what you will learn throughout the 7 weeks course.
PROGRAMMING COMPETENCIES
Learn how to perform analysis with the use of popular programming languages like Python
STATISTICAL MODELLING
Use standard analysis models to generate useful information and provide actionable insights
DATA VISUALISATION
Aggregate and visualise data using data libraries in Python to display information to audiences in a useful manner
- Project 1: Exploratory Analysis (Due on Week 2)
- Practice exploratory data analysis on movie dataset
- Required to present approach on week 2
- Project 2: Visualisation of Food Data (Due on Week 4)
- Practice data visualisation concepts and libraries 1b
- Required to present approach on week 4
- Project 3: Scraping Job Data (Due on Week 5)
- Practice web scraping libraries and concepts
- Required to present approach on week 5
- Project 4: Yelp Reviews (Due on Week 6)
- Students are to use libraries learnt to perform text mining on Yelp reviews
- Required to present approach on week 6
- Project 5: Passenger Survival Project (Due on Week 7)
- Consolidation project where students will be able to apply the concepts they learn from the lessons, specifically, Lesson 1, Lesson 2, Lesson 3, and Lesson 6
- Required to present approach on week 7
Instructors
Darren Tan
Software Engineer @ PSA
Singapore Management University Information Systems
Instructors
Raymond Li
Data PM @ Shopee
Columbia University (New York)
Management Science & Engineering
Instructors
Sherman Koa
Software Engineer @ Visa
Singapore Management University Information Systems
GOVERNMENT SUBSIDIES
Our courses are $2000 before subsidy. Students are eligible for course subsidies under the CITREP+ framework. Subsidies ranges from 70% to 100% depending on which tier you fall under.
CITREP+ supports local professionals in keeping pace with technology shifts through continuous and proactive training.For more information, you can visit the IMDA website here for more information.
STUDENTS’ TESTIMONIALS
Check out what students have to say about our courses.
Wenyu See
The environment was really conducive for learning: spacious, with all the necessary amenities. Besides that, the instructor was very passionate, and was well-prepared for class with in-class worksheets to guide. During the lesson there were also teaching assistants who went around the room to provide guidance when help was needed. The TAs contactable via telegram chat should you require any assistance with your homework.
Foo Rong Chang
Excellent course where instructors are both knowledgeable and passionate. There are teaching assistants walking around to assist you in your learning and are more than willing to go out of their way to help you in other languages as well should you need the help. Helpful, friendly and approachable are the traits that they possess and have made the learning journey for us students so much easier and more fun as well!
• CAREER SERVICES •
Our career services department works with student graduates to improve their career chances.
Linkedin Digital Cert
Each of our courses grants you a digital cert that is LinkedIn-compatible. You can now display your qualifications globally.
Career Matching
We work with partners who actively tries to link our graduate to internships and jobs.
Industry Networking
Network with your instructors who are from within the industry.
Get your answers to questions you may have about the bootcamp.
What is Data Science?
Data scientist performs research and analysis on data and helps companies to improve business by predicting growth, trends and insights based on huge amounts of data.
Why Learn Data Science?
Data Science was voted as the #1 Job of 2016 by Glassdoor and demand for Big Data jobs are expected to increase up exponentially in the future.
What is the Expected Pay of a Data Scientist?
Data Scientists earn an estimated mid-career salary of $104,000 annually.
My company has data science problems, what do I do?
If your company has seemingly huge amounts of data, learning data science skills will allow you to manipulate that data into actionable insights. Should the problems be tough to solve, our experienced instructors can solve your data science problems together in the capacity of a consultant.
Danial Adam Leong
The instructors are highly knowledgeable to be able to bring across new concepts as well as to explain the practicality of the concepts in the workforce! The atmosphere was also very conducive with meals and drinks being offered. Their follow-up service is also impeccable as they continue to update previous classes regarding new happenings in the data science field. Overall, it was a blast and I'm glad to have signed up for it!