Humans have an insatiable nature. This trait can of course be a double-edged sword for humans themselves depending on how they are used. Scientists are part of humans who have an insatiable nature and apply these traits to positive things, they continue to create knowledge that can continue to make life easier for us, one of the revolutionary innovations is Data Science.
Thanks to Data Science, many technologies have emerged, making it easier for humans to carry out their activities. In addition to the many innovations provided by Data Science, this science also makes it easier for humans to store data, so that data can be used effectively and efficiently. Of course, with the development of this science, we could be one step closer to achieving what we have not yet achieved which is still everyone’s dream, such as flying cars, landing to mars, and so on.
We have often encountered Data Science in our daily activities but often we are not aware of the existence of the results of this Data Science. Here are the results of the innovations developed by Data Science.
1. Machine Learning
Machine Learning is a machine that was developed to be able to learn by itself without the help of the manufacturer. Machine learning includes other disciplines such as statistics, mathematics and data mining.
Machine learning is a branch of the formation of artificial intelligence (AI). In an AI a lot of machine learning is needed to obtain existing data and study that data in order to perform certain tasks.
Surely some of you are still confused about machine learning, how they learn and develop themselves. Just like humans, machine learning has various learning techniques, namely supervised and unsupervised learning.
- Supervised Learning
This technique is usually used on goods that have complete information. Machine learning will label the item according to the same categories and also place it according to that category. This technique aims to provide a target for the output carried out by comparing experiences from the past
- Unsupervised Learning
In contrast to supervised, this technique is used when the information regarding the item is incomplete. So that machine learning does not yet have a reference for labeling goods. This technique is used to search for certain structures or patterns that do not have labels.
Of course, machine learning also requires maintenance that is not easy, this is where the task of a Data Scientist is to make sure everything runs smoothly and properly.
2. Artificial Intelligence (AI)
Artificial intelligence or better known as artificial intelligence (AI) is a machine programmed to think like humans or their actions. AI itself was created in 1956, although it is only 65 years old but AI is highly developed due to the volume of data, advanced algorithms, and increased computing power and storage.
The following are the benefits provided by using AI technology:
- Minimizing Errors
AI is able to work with a high degree of accuracy, and is consistent. This of course will minimize mistakes that are usually made by humans. AI can also study large amounts of data to make the best decisions. Therefore, its use can take action in order to minimize the risk of loss. - Speed Up Time at Work
In the AI process there are terms learning, reasoning and self-correction. These three points will make artificial intelligence have broad knowledge. So, artificial intelligence can get the job done faster. - Doing Human Tasks
If your house carries the concept of a smart home, Google and Alexa are an important component, they are assigned as your personal assistant. Simply give the Ok Google command to activate it then give a command like “Turn off the light” and tadaaaaa your lights will be turned off by Google.
Although AI itself has a myriad of benefits, we also have a big challenge to develop AI itself. AI can learn only using data there is no other way to enter knowledge in the absence of data. That’s what causes data processing to be precise if the data processing is not correct it will be reflected in the answers generated by AI.
AI also has drawbacks, namely that it has to do certain tasks, AI cannot do tasks that do not have clear rules, such as detecting fraud or providing legal advice. Unlike the AI technology that we see on the big screen, where AI Robots can have feelings and even behave like humans.
3. Big Data
Big data is a larger and more complex collection of data, especially from new data sources. These data sets are so large that traditional data processing software cannot manage them. However, this vast amount of data can be used to address business issues that you couldn’t previously handle.
One of the most easily understood explanations of data is the collection and use of information from multiple sources to make better decisions. Big data can be considered as a concept about our ability to collect, analyze, and understand the sizable amount of data that comes in every day.
Big data is also useful for sources that are drawn by data-driven technologies. Without complete data, AI and machine learning will fail to understand what to do, because they act according to existing data, if the data is inaccurate, the results will not be accurate.
Take Part in Developing Innovation by Learning Data Science
DQLab is a Data Science learning center that offers online courses for those of you who want to start learning Data Science. DQLab itself has produced data practitioners who are proficient in their fields. With DQLab you will learn in a structured manner with case studies and data that are in accordance with those in the field. DQLab also provides a forum for sharing with 95,000++ members of DQLab, as well as with expert data practitioners.
So, there is a real need for DQLab to hold a mini bootcamp for you, especially for those of you who are preparing for the Merdeka Campus Program. For more information, you can directly click the link below.
Info Lengkap Mini Bootcamp DQLab x UMN
The registration period to take part in the DQLab Mini Bootcamp is from 19 – 28 November 2021. The quota for participants is very limited, register yourself immediately to take part in the DQLab Mini Bootcamp and be ready to face 2022 as a data literate student.
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