Data Science 101
Multiple Dates Available | Daily Lessons or Weekly Lessons | S$2000 (Up to 100% Subsidies Available)
Learn Python For Data Science Over 7 Weeks (Or Less!)
Why Learn Data Science?
Have you ever shopped online and found advertisements strangely related to what you’ve been searching for on Facebook and other websites continuously for a week? Or say, you’re texting with your friend and the keyboard suggests to you the exact words that you were going to use in your sentence? How does YouTube show all your favourite videos on your homescreen?
In business, Data Science is successfully adding value to all business models by using statistics and deep learning to make better decisions and improve hiring. It is also being used to crunch historical data and predict possible situations or risk so that we can work on avoiding them.
Data Science Track
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.
DS101 COURSE DETAILS
DS101 will be held once a week over 7 consecutive weeks. Each session would be 3 hours long heald at 991D Alexandra Road #01-22/23 Singapore 119972. The courses fees is $2000 before subsidy, however Singaporeans and PRs are eligible for subsidies of up to 100%.
Find out what you will learn throughout the 7 weeks course.
Project 1: YouTube (Due on Week 4)
- Familiarise with storing data into python data variables
- Practice writing scalable python codes to extract intermediate output from data
- Practice applying conditional changes upon the data set
Project 2: Lazada (Due on Week 5 & 6)
- Practice writing modular codes
- Learn how to clean the data using python programming
- Learn how to extract even more complex outputs from the data using python codes
- Learn how to perform basic visualisations through using python
Project 3: Airbnb (Due on Week 7)
- Serves as a consolidation for all the concepts students have learnt
- Learn how to leverage upon complex python libraries to deliver intermediate outputs and visualizations
- Gain an insight into how python programming can be applied upon real data to derive at useful actionable insights
Lecture 1a: Introduction to analytics
- Be cognizant of the business uses cases for data science and data analytics
Lecture 1b: Python Expressions & Variables
- Declare variables, and manipulate the variables to perform arithmetic operations
- Variable conversion
- String slicing
- Concatenate string & other non-string variables
- Special characters
- Debugging python programs
Lab Exercise 1 (Due on Week 2)
Lecture 2a: Decision Structure & Boolean Logic
- Sequence structure
- Boolean operators (conditional & relational)
- IF, ELIF, ELSE constructs
- Nested decisions
- “Not” operator
- Lecture 2b: Collections
- List (Access, append, remove, update)
- Tuple (Access, append, remove, update)
- Dictionary (Access, append, remove, update)
Lab Exercise 2 (Due on Week 3)
Lecture 3: Iterations Part 1
- While loops (indefinite)
- Infinite loops
- Using break
- for loops (definite)
- Finding the largest/smallest
- Filtering results
- Use of “Is”, “not” and “in”
- Range for loop
- Iterating through a dictionary
Lab Exercise 3 (Due on Week 4)
Lecture 4: Iterations Part 2
- How is iteration used in data science?
- Consolidate understanding of iterations with a series of practice questions
- Apply iterations to create advanced algorithms (eg. consolidating data in a unique hashtable)
- Nested iterations
Lab Exercise 4 (Due on Week 5)
Lecture 5: Functions
- How to write and invoke python functions
- How to leverage on commonly used Python libraries (eg. Math, Statistics, Regular Expression)
- How to perform visualisation using Matplotlib
Lecture 6: Applying Programming into Analytics using Lazada as a Case Study
- How to read & write csv into python collections
- Answering analytical query using Python
- Simple visualisation using Matplotlib
Project Assignment (Due on Week 7)
Lecture 7: Consolidation & Closing
- Go through answers on the Airbnb Project
- Consolidate understanding with a series of in-class programming questions (will be done in a competition game format)
- Closing & the way ahead for students
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.
Check out what students have to say about Hackwagon’s courses.
Daniel 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!
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 are 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!”
Our career services department works with student graduates to improve their career chances. As an IoTalents Academy – Hackwagon graduate, you receive exclusive career matching services with contemporary tech recruitment firm IoTalents. Get trained and placed in attractive data science jobs with IoTalents.
LINKEDIN DIGITAL CERT
Each of our courses grants you a digital cert that is LinkedIn-compatible. You can now display your qualifications globally.
All IoTalents Academy students get superior career matching support through IoTalents’s tech recruitment concierge platform and jobs marketplace.
Network with your instructors who are from within the industry.
GET YOUR ANSWERS TO QUESTIONS YOU MAY HAVE ABOUT THE COURSE.
What is Data Science?
Data scientists perform 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.