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Each course spans over eight (8) weeks; includes informative and interactive lectures, discussion, practicals, and activities. Participants will be guided in the application of what they have learnt during the Bootcamp to the real world data and scenario(s). Below are the structures of courses offered in our Bootcamp:
|Course name||Applied Regression & Time Series|
|Description||This course emphasizes the concepts and the analysis of data sets with the application of key concepts, which are simple linear regression, multiple regression and matrix operations. Besides familiarise these two approaches, all the participants will reinforce the concepts in the real data sets and explore as well as evaluate the suitability of the selected regression variables and geometric interpretations.|
|The skills/tools you will gain/learn||R, Linear Regression, CART|
|Course name||Big Data|
|Description||With the voluminous amount of data, this course aims to prepare the participants to enable dealing with large-scale data analysis. The patterns, trends and associated technologies will be exposed to all participants with both theoretical and hand-on approaches. So that, at the end of the course, they able to understand the application of big data in emerging areas of technology.|
|The skills/tools you will gain/learn||Apache Spark, Hadoop|
|Course name||Business Intelligence|
|Description||Business Intelligence plays a central role in an organisation to handle large amounts of data and information as well as assists for the decision-making. With a brief understanding of BI concepts and principles, this course provides a demonstration platform to enable all participants to appreciate the business development model through the lens of a data-driven organisation.|
|The skills/tools you will gain/learn||BI Analytics Software|
|Course name||Data Analytics Essentials|
|Description||It is a pretty great success in any field by turning data into clear insights that support effective action, problem-solving and decision making. This course is intended to provide a better platform to apply the data analytics and statistical computing skills in real data besides preparing all participants with a brief idea of data visualisation and data preparation for analysis.|
|The skills/tools you will gain/learn||R, tibbles, Python, pandas|
|Course name||Data Driven Organisation (DDO)|
|Description||Robust data in an organization are critical for data analysis and decision making. This course will introduce students to the shift in organizations in being data driven, leveraging on technological convergence to propel their vision and mission by developing the necessary skills to incorporate the results of data analysis within the decision-making process.|
|The skills/tools you will gain/learn||Conceptual framework for DDO|
|Course name||Data Visualization|
|Description||Data visualization is an important visual method for effective communication and analyzing large datasets. A well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. Through this course, all the participants will get the exposure of the visual techniques and visual aids application.|
|The skills/tools you will gain/learn||ggplot, matplotlib, d3.js|
|Course name||Digital Marketing|
|Description||Digital Marketing or data driven marketing is product and services marketing using digital technologies. Understanding of sales and marketing function, use of contemporary digital tools and data analytics is needed to develop and operate a digital marketing program. This course will provide all the participants with a brief exposure to development, use of digital technologies and data analytics in sales and marketing function.|
|The skills/tools you will gain/learn||Marketing principles, Strategies|
|Course name||Dimensionality Reduction|
|Description||Dimensionality reduction is often performed in machine learning and data mining on big data. This course aims to guide all participants the awareness of main approaches and the issues. A better understanding of its algorithms and techniques to real datasets will enable the participants to appreciate the importance of this course.|
|Applied algorithms for dimensionality reduction|
|Description||With the concept of applying the statistical and mathematical analysis of economic data, this course provides a platform for all the participants with the knowledge of empirical content to economic relations. In particular, this course will equip the participants with the fundamentals of economics and application of mathematical tools in the field.|
|The skills/tools you will gain/learn||Econometrics and analysis methods|
|Course name||Health Analytics and Data Mining|
|Description||Health analytics plays a vital role in the healthcare field to efficiently extract and capture as much as possible fruitful information due to the tremendous public health data. This course provides a foundational knowledge of analytics with covering health information systems, data mining methods and strategies in performing data analysis. The ultimate goal of this course equips all participants to effectively contribute their analytics knowledge towards healthcare project to improve the healthcare.|
|The skills/tools you will gain/learn||PCA, data mining techniques, and machine learning|
|Course name||Introduction to Data Science and Toolkits|
|Description||Data Science is the study of the generalized extraction of knowledge from data. This foundation course aims to provide a brief and clear understanding of data science’s ideas or concepts and the toolbox as well in both conceptual framework and hands-on practical. This course will equip the participants with effective problem solving skills to prepare them deal with various data science problems out there.|
|The skills/tools you will gain/learn||Graphs, Matrix factorisation, Python and R for Data Science|
|Course name||Machine Learning|
|Description||Machine learning is an emerging field of artificial intelligence that interfaces statistics and computer science. This course will provide the participants a platform to understand the ideas, develop the machine learning skills and apply the knowledge in life science/healthcare especially those popular research field of pharma and medicine include precision medicine and epidemic outbreak prediction. This algorithm allows the computer systems to learn from data and make decisions with minimal human intervention.|
|The skills/tools you will gain/learn||Hierarchical Clustering, Linear regression, Neural networks|
|Course name||Web Programming and Scraping|
|Description||As web development has become an essential step, this course is designed to guide all the participants on a path towards the study of web development and design using HTML, CSS, API etc. With that knowledge, the participants able to execute data fetching and extraction from World Wide Web.|
|The skills/tools you will gain/learn||Scrapy|
*Bootcamp courses/topics are subject to changes as Data Sciences is an emerging field.
*Participants are advised to bring your own device(s).
*There’s an additional one hour optional consultation session on the weekend to discuss the problems that the participants may have experienced when doing the practical.
(Jan – Feb)
(Apr – May)
(Jul – Aug)
(Oct – Nov)
|Introduction to Data Science and Toolkits|
|Data Analytics Essentials|
|Web Programming and Scraping|
|Applied Regression & Time Series|
|Health Analytics and Data Mining|
|Data Driven Organisation (DDO)|
|Category||Rate (MYR) per course|
Block B, MAEPS Building, MARDI Complex
Jalan MAEPS Perdana, 43400 Serdang
The number of hours are as below and are the same for each course:
No. of face-to-face hours per course = 8 topics x 4 hours = 32 hours
No. of self-study hours per course = 8 topics x 6 hours = 48 hours
Total hours per course = 80 hours (over a period of two months)
For each topic of each course, we will conduct a two-hour lecture session (6.30-7.30pm, with dinner/prayer break from 7.30-8.00pm, and continuation of lecture from 8.00-9.00pm) on the designated course day (see Table in Query #1 above), followed by an hour of practical on the same day. The students are to use the remaining weekdays for completion of the practical and self-study. An additional one hour (optional) consultation session will be conducted every Saturday (a time convenient for the students to be finalised on the first day of class) to discuss any problems that the students may have encountered during the practical or other questions related to the practical/lecture.
Example: All the topics of course 1 will be taught on Mondays. For each topic, the class will start with a two-hour lecture, followed by one hour practical. Students then spend the remaining weekdays to complete the practical and do a self-study on the lecture material covered. The students will meet the instructor again on Saturdays for an hour of consultation on the practical/lecture or other related questions.
Yes, a certificate of participation will be given to each participant of the course.
Maximum of 20 participants.
Registrations are open till a day before the start of the intake month (e.g. last day of Feb for March intake). However, registrations are on a first-come, first-served basis and will be closed if the maximum number of participants is reached.
We can make arrangements for this if a request is made earlier. Also, it would be preferred if the students travelled together, so multiple trips can be avoided. Alternatively, public transports are convenient and the students can opt for KLIA Ekspres, bus or budget taxi to reach their accommodation place.
The cost is estimated to be between RM375 and RM500 per month depending on the size of the bedroom. Please contact Student Services Department for more information.
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