Malaysia Assignment Helper Klein

Big data is on an upward trend throughout the world and companies are constantly on the lookout to find the right talent with the right skill sets in order to succeed in the changing marketplace.

On the home front, the Malaysian government, positioned as a data driven nation, aims to create 20,000 data professionals by 2020.

In line with this objective, The Centre of Applied Data Science (CADS) has collaborated with Coursera, a massive open online course (MOOC) platform to offer numerous data science courses to Malaysians.

The partnership was consolidated recently through a Memorandum of Understanding (MOU) between CADS managing director Cheam Tat Inn and Coursera International Government Partnerships manager Matthew Klein.

Cheam said: “We are delighted to partner with Coursera, as we believe this collaboration will enable us to nurture and empower a new generation of data scientists who will have access to the world’s best online education. The platform will enable Malaysians to pursue their education without having any restrictions and problems.”

Coursera was founded in 2012 by two Stanford University Computer Science Professors; Daphne Koller and Andrew Ng. With a vision for harnessing technology to empower people with access to education, they offered their first open online courses through Stanford in the fall of 2011 reaching enrolments of over 100,000 each.

The collaboration offers extensive learning in data science and related topics, further allowing individuals to have internationally recognised accreditation without having to leave Malaysia. This is achieved as Coursera complements a broader learning experience by bringing the campus to individuals and their workplace.

Klein said: “We are extremely pleased to be working with CADS to create an opportunity to make high-quality, cost-effective data science learning accessible in Malaysia.

“The CADS partnership is really unique in its blended learning offering to participants, allowing them to benefit from our wide range of courses on data analytics from top-tier university and industry partners, as well as utilising personalised mentors to create a really innovative effort that will generate a critical talent pool for data scientists in Malaysia.”

Coursera courses include short videos interspersed with quizzes, targeted assignments and discussion forums with a global community of peers. Most courses have regular start dates and are self-paced with suggested deadlines to keep learners on track to reach their goals.

CADS aims to bridge the knowledge gap and fulfil every possible skill set required in a data driven industry through its collaborations with Harvard Business School, The Data Incubator, Data Star and Coursera.

CADS is a delivery partner for Project Data Star, a six-month finishing school programme for graduates. It includes two months of intensive data science enablement and mentorship with experienced data scientists and placement at industry partners. The project is driven by ADAX to partner with universities and leading industry partners to fast track the development of industry-ready data professionals.

“This signifies our commitment in having a highly skilled pool of data scientists who are exposed to courses from international universities. Among the reputable institutions are John Hopkins University, Wharton University of Pennsylvania, University of Washington, and University of California, San Diego,” Cheam added.

The curriculum covers everything from management roles to analytic, engineering and career roles like data scientists, data analysts and data engineers. They can complete the one-year online education programme by taking advantage of the 11 online courses of international standards, offered by premier global institutions. Students will also have access to CADS Learning Hubs coupled with weekly personalised tutoring session with highly trained and experienced data scientists.

Also present at the event were ADAX chief executive officer Sharala Axryd and MDEC Data Economy Division director Dr Karl Ng Hou.

Sharala said: “A MOOC platform like Coursera proves to be a valuable tool in an individual’s arsenal. Organisations have placed more importance on reskilling and upskilling as they demand proficiency in new technologies. Utilising online courses can lead to fulfilling careers through expanded learning for university students, career progression for working individuals and a sustainable workforce for employers.”

The course will begin in February 2018 and is priced at RM4,999 for working professionals and RM3,599 for students. The fee covers examination and quizzes, lab access and the guidance of a data scientist an hour per week throughout the whole learning process.

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A Brief Description of Statistics

Statistics is the branch of mathematics that deals with the analysis, interpretation, processing and presentation of data using statistical formulas and concepts. Statistics is also used to draw an inference from a given data set. In simple terms, it is a subject that brings out logical meaning from complicated mathematical data. Statistics is broadly divided into two parts, namely; descriptive statistics and inferential statistics.

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It is a diverse subject, which has lots of breathtaking formulas and steps. It is broadly divided into two main parts: Descriptive and Inferential.

  1. Descriptive Statistics - It can be defined as procedures used to organize, summarise and interpret a set of observations and scores. Descriptive statistics is purely related to the properties of the observed data and does not assume that the data came from a larger population. It is generally presented graphically in tabular forms or in single values. In this sort of statistics, data is analyzed by the central tendency fundamentals such as the mean, mode or median. To learn more about this type of statistics take the assistance of our expert writers and subject matter experts in our service statistics assignment help.
  2. Inferential Statistics - It can be defined as the procedures that allow researchers to figure out and generalize the observations made with the sample to the larger population. To draw inferences, this comprises of selecting the statistical model of the process which generates the data and concluding propositions from the model.

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  • Run an ANOVA using Overall Satisfaction

    Is there a difference in the overall satisfaction of women based on the number of housing problems (no problems, 1 problem, 2 or more problems)? Using Polit2SetA data set, run an ANOVA using Overall Satisfaction, Material Well- Being (satovrl) as the dependent variable and Housing Problems (hprobgrp) (this is the last variable in the data set) as the independent variable.


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