DATA SCIENCE TRACK

DATA SCIENCE 101

Build your foundations in the tools-of-the-trade (python) over 7 weeks.

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DATA SCIENCE 102

Learn to perform data exploration, visualisation, and machine learning using advanced python libraries.

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DATA SCIENCE 103

Learn to build an enterprise level end-to-end data analytics model with a data pipeline.

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The Data Science 102 (DS102) course is where students can learn about data analytics toolsets in Python. In our master class, Data Science 103 (DS103), students will graduate with data know-how in an organisation setting and be certified as a data analyst by our academy.

WORK ON REAL DATA

We are exceptional at bringing students from beginners to professionals. Expect to graduate with the ability to perform deep and insightful analysis. Below are some of our students' project:

SENTIMENT ANALYSIS AND NAIVE BAYES CLASSIFICATION ON E-COMMERCE REVIEWS

One challenge that businesses face is how to gain a better understanding of the voice of the customer. This issue can be addressed by extracting additional information from customer reviews, using sentiment analysis.

HEALTHCARE SUSTAINABILITY THROUGH DOCTOR/BED-PATIENT ANALYSIS

We analyse the number of doctors and hospital beds against the number of admitted patients between 2006 to 2015 to see if the Healthcare sector is sufficiently equipped to support the number of admitted patients.

RELATIONSHIP BETWEEN SINGAPORE’S RESERVE AND CPF BALANCE

This project aims to visualise both Singapore’s Total Foreign Reserves and CPF balance from 1972 – 2015 with the objective to determine if Foreign Reserves growth can be explained by growth in CPF balance.
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Wundercell

Our data analytics platform to improve your learning experience and apply what you have learnt to the workplace.

  • Collaborate

    Work on a shared Jupyter notebook, while maintaining the ability to navigate and work independently

  • Dashboard

    Build a realtime dashboard with live data and analysis straight from your notebook

Develop your potential
Seek out correlations with machine learning and create visual representation of the data to communicate information effectively.
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COURSE DETAILS

DS102 consist of 7 lessons with each session lasting 3 hours long at 991D Alexandra Road #01-22/23 Singapore 119972. The course fees for the course is $2000. Discounted prices available for corporate runs of the DS102 public course (without Govt Subidies).

Prerequisites Required
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.

Covid-19 Measures
In light of the Covid-19 situation, the July cohort are tentatively planned for either live stream format or physical classes depending on the government's direction closer to the course start date. Live stream lessons will be supplemented with weekly small group online consultations with the teaching assistants.

*Course schedule can be found by clicking Apply Now or here.
 

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 like list, dictionaries and 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.

 

CURRICULUM

Find out what you will learn throughout the 7 weeks course.
  • 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

Yi Sheng Data Engineer at Fullerton Health Singapore Management University SMU Salutatorian
Jishnu Mohan Data Science Instructor National University of Singapore Computer Sci, Honours with High Distinction
Wei Han Zheng Software Developer at Stashaway National University of Singapore Computer Sci, Honours with Highest Distinction
Danielle Thio Data Analytics Instructor National University of Singapore BSc in Quantitative Finance
Thomas Odell Data Analytics Instructor University of Toronto Honours B.A. Computer Science
 

CLASS SCHEDULE

You can be kept updated when we release new class slots through our telegram group here, https://t.me/hackwagon.

Our latest class schedule for Data Science 102 (DS102):

STUDENTS' TESTIMONIALS

Check out what students have to say about our courses.

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!

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!

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.

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