Intro to Data Science - Crash Course for Beginners

Learn the basic components of Data Science in this crash course for beginners.

In this course for beginners, you will learn about:

1. Statistics: we talk about the types of data you'll encounter, types of averages, variance, standard deviation, correlation, and more.

2. Data visualization: we talk about why we need to visualize our data, and the different ways of doing it (1 variable graphs, 2 variable graphs and 3 variable graphs.)

3. Programming: we talk about why programming helps us with data science including the ease of automation and recommended Python libraries for you to get started with data science.

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:10:52) Statistical Data Types
⌨️ (0:25:10) Types of Averages
⌨️ (0:38:55) Spread of Data
⌨️ (0:50:54) Quantiles and Percentiles
⌨️ (0:55:52) Importance of Data Visualization
⌨️ (1:05:14) One Variable Graphs
⌨️ (1:12:04) Two Variable Graphs
⌨️ (1:25:08) Three and Higher Variable Graphs
⌨️ (1:31:20) Programming

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[galenseilis]

This video is for people unfamiliar with basic statistics because it focuses on introductory estimators of central tendency, types of data, and data visualization.

[andersonm]

Quantitative Research Methodologies Q&A
1. Evaluate the scope of quantitative research methodology comparing each method and critique each technique, model, metaphor, and paradigm. 200 words
Ethnographic studies are commonly used in research methods. The model of ethnographic studies is based on the researcher following participants or subjects into their culture to gain more insight into cultural issues. A metaphor of an ethnographic study is following customers to their home to understand why they purchase a given product and not another. The three paradigms of ethnographic studies include behaviorist, semiotic, and holistic styles. Interviews and surveys are the specific techniques embraced in ethnographic studies (Park, & Park, 2016).
The narrative method includes the use of two main techniques; interviews or collecting information from person’s documents that include diaries, memoirs, and other personal encounters narrative documents. The narrative is selected carefully to be a metaphor of the whole population, for instance, someone narrating how a calamity strikes their community might be narrative that can tell what the whole community experienced. The models of narratives can be spoken, written, or visually represented. The paradigm is that what one person experienced does not differ significantly from what the rest of the community experienced concerning the specific problem being analyzed (Park, & Park, 2016).
The third methodology is the phenomenological study which embraces multiple techniques that include interviews, surveys, literature review, and others to describe phenomena. The main models embraced in the phenomenological study include purposive sampling and systematic sampling. The metaphor of this method is that the collection of data from varying sources will give a united theme and data relevant to understanding the phenomena. The paradigm, hereby, is that the collected data about a certain phenomenon will show common features about the phenomena (Park, & Park, 2016).
The fourth method is grounded theory. It is closely associated with the phenomenological study in that it embraces the use of varying sources of information to develop a theme and collect data about phenomena. Its techniques, models, metaphor, and paradigms are similar to those of the phenomenological study (described in the paragraph above), but unlike phenomenological studies that look into the essence of an event or activity, the grounded theory seeks to give theories or explanations behind an occurrence or event (Park, & Park, 2016).
The fifth quantitative research methodology is the case study method. This method looks into occurrences as they affected a subject or few subjects. The techniques in this method include a single subject case study or multiple subjects’ case studies. The models of inquiry may include interviews, observations, or literature review for past events case studies. This model has a paradigm that what happens to one person applies to other people with a similar problem in society (Park, & Park, 2016).

2. Select the best quantitative method and assess the strengths and weaknesses of that selected method defending why the selected quantitative method is the best. 80 words
The best qualitative method in my opinion is an ethnographic study. Given my interest in social science, I find that understanding the behavior of a given group through interacting with the group is the best model to use. Moreover, unlike case study design this method allows for interaction with a larger number of participants or subjects with similar concerns. Moreover, it is a method that develops a hypothesis that can be approved or disapproved by the research, unlike the phenomenological and grounded theory designs that look for common themes during the active research. One of the weaknesses of ethnographic studies is that it can consume a huge amount of time. The researcher can also be faced with great challenges fitting in with a new culture and gaining their trust after s/he declares interest to understand their cultural elements.

3. Compare various quantitative methods and how each method enables researchers to design the correct series of questions and eventually hypotheses to prove the theories. 120 words
The ethnographic study follows researchers into their cultural roots to understand their behavior. It is appropriate for cultural studies that aim to understand behavior such as consumer behavior. The narrative aims at gaining opinions from specific subjects, or their encounters concerning a certain problem. It closely relates to the case study design which also focuses on individual’s stories. These two methods can yield results in understanding people’s reactions to certain societal problems, for instance, the experiences that parents undergo after losing a job. The phonological studies and grounded theory methodologies are similar in many aspects including the fact that they seek a common theme from multiple sources of information such as interviews, literature, surveys, and other sources. However, the grounded theory seeks to explain or develop a theory describing a certain societal concern, while the phenomenological study looks into the essence of the societal concern of interest.
The ethnographic study, case study, and narrative begin with preparations that include the identification of the societal problem, development of research questions, and a hypothesis that the study will either approve or disapprove. The phenomenological study and the grounded theory designs, on the other hand, have a planning process that only includes the identification of the problem and sources from which information will be obtained. These two quantitative methodologies develop a common theme in the field of study, which gives research questions to be responded to and maybe a hypothesis which is not mandatorily essential.

[carmelinaroig]

Awesome video! I learned a lot and very useful. Thank you so much!!

[curtistheuniverse]

Excuse me im kinda new to this thing i have a question do i need paper for all of your data videos or anything or can i just watch the video??

[thesohelshaikh]

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:10:52) Statistical Data Types
⌨️ (0:25:10) Types of Averages
⌨️ (0:38:55) Spread of Data
⌨️ (0:50:54) Quantiles and Percentiles
⌨️ (0:55:52) Importance of Data Visualization
⌨️ (1:05:14) One Variable Graphs
⌨️ (1:12:04) Two Variable Graphs
⌨️ (1:25:08) Three and Higher Variable Graphs
⌨️ (1:31:20) Programming

[CRiver]

I wish this was pratical. I can't find any tutorials that use simple language when talking about data science.

[Gnosis]

I learned all this as a psychology student. I had no idea I was also being trained as an data scientist lol

[michaelolz]

Amazing, amazing job! Nice touch with the stock photography, which looks to be original. Learned a lot from this one. Keep it up!

[lionking]

😂😂😂 hum..yah...I see the data goes up and down...that was funny!!!

[DesignerGuy]

I wish there was a scholarship offer (or some deferred payment option) for those of us in the developing world who can't afford to pay for this training but are sooo interested in learning Data Science.

[itiswhatitis]

Coffee production can indeed have a notable impact on climate change, primarily through the following factors:

Firstly, coffee cultivation often requires deforestation, especially in regions like the Amazon rainforest. The removal of trees, which act as carbon sinks, results in the release of stored carbon dioxide (CO2) into the atmosphere. This contributes to higher atmospheric CO2 levels, a major driver of global warming.

Secondly, coffee farming relies heavily on water resources, and inefficient water use can lead to ecosystem degradation. In many coffee-producing regions, unsustainable farming practices, such as excessive irrigation and chemical fertilizers, can contaminate water supplies and harm aquatic ecosystems. The disruption of these ecosystems can further exacerbate climate change by releasing methane (a potent greenhouse gas) and reducing the planet's natural ability to regulate its climate.

Finally, coffee is often transported over long distances, consuming substantial energy and emitting greenhouse gases during transportation. This adds to the carbon footprint associated with coffee consumption, as emissions from shipping and logistics contribute to global warming.

In summary, while the link between an individual's cup of coffee and immediate climate change may seem distant, the cumulative impact of widespread coffee production practices, including deforestation, water use, and transportation, can play a role in contributing to climate change when viewed at a global scale.

So it may affect it will rain or not depending on no. of cups if coffee we drink ....


Just kidding!! :)

[AndreaGarcia-qejz]

What can be the “data” can someone give an example? I understand it can be *anything* but like what? A persons personal info or what

[HanifCarroll]

Awesome video, thanks for putting in the effort to make this! It's funny, I was totally uninterested in anything to do with math or statistics while I was in school, but now I think this stuff is really cool! Being able to use data to learn from the past and guide your actions in the future...what's not to like?

[ModulAcAtuniversity]

Very helpful video - we can also recommend to study Applied Data Science at MU Vienna - small class sizes and great professors! Check out our curriculum.

[raypenbar]

Awesome breakdown on this topic Max! I have my roots in physics as well and went into it-consulting a few years ago. I have been looking for good introductions on this topic. For me it was so much easier to follow the explanations coming from a physicist. Thanks for that!

[solarp]

weird how i cannot hear anything from this video. Damn how do i fix this...

[vectoralphaSec]

So as someone who eventually one day wants to work in data science industry, is there an entry level job role that one can apply as a starting point and just get promoted/ level up to a data science in time rather than just trying to apply for a data science position from the get go? I dont mind starting at the bottom and working my way up the ladder.

[arniyhjs]

Hello Max, it's a beautiful thing you are dong. I just want to ask, what are the most recommended websites, books or podcast to learn Data Science because sometimes surfing through the web to get an efficient and effective training can be a bit overwhelming. BTW I really love Data Science and I hope one day I will be training others as you are. Thanks.
Love from Nigeria.

[Erik-fgfk]

Why should a weight of an adult be a discrete numerical value ? I mean If I put a cheeseburger in my mouth in ones, I’m jumping from 70kg instantly to 70, 3kg or am I wrong ?

[Michael-vzcy]

I don't follow quartiles: there are four quartiles, but only three listed (at (52:12). I didn't follow the explanation for that. Maybe display it by listing all four?