Intro to Data Science – Crash Course for Beginners




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Learn the basic components of Data Science in this crash course for beginners.
If you want to learn more about data science after completing this course, check out Max’s Free Getting Started with Data Science Workshop: https://codingwithmax.com/webinar/data-scientist/

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

Course from Coding With Max. Check out the Coding With Max blog: https://www.codingwithmax.com/blog
Full data science course: https://codingwithmax.teachable.com/p/data-scientist-10-weeks

Learn to code for free and get a developer job: https://www.freecodecamp.org

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And subscribe for new videos on technology: https://youtube.com/subscription_center?add_user=freecodecamp

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Comment List

  • freeCodeCamp.org
    November 16, 2020

    Hey everyone! This is Max from the course – thanks so much for checking it out. 🙂 We've got a ton of free resources over on the blog and my website at codingwithmax.com to help those of you who are curious or want to learn more.

    I hope this mini-course gives you a good basic insight into what the term 'data science' exactly entails, and I also hope it piques the curiosity in some of you to look into a career in data science!

    If you want to dive right into it, my full Data Scientist in 10 Weeks course can be found here: https://codingwithmax.teachable.com/p/data-scientist-10-weeks

    If you have any questions, please don't hesitate to let me know! I'll definitely hang around here and check for any questions or comments. 🙂

  • freeCodeCamp.org
    November 16, 2020

    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.

  • freeCodeCamp.org
    November 16, 2020

    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.

    4. Recommend best methods to solve different types of analysis and provide a table that outlines each method, what type variables are used, best applications, and what findings to expect. 100 words

    Descriptive analysis Predictive analysis Diagnostic analysis Prescriptive Analysis

    Recommended Method Case study, cross-sectional research, surveys, naturalistic observation, archival research, and longitudinal research Analytics techniques such as regression models, time series, and others. Case studies, questionnaires, interviews, surveys, and observations Mathematical learning and machine learning methods

    Types of Variables Descriptive variables such as “agree or disagree” Predictor variables; variables linked with certain outcomes such as regression variables Descriptive variables such as a scale of 0-10 in rating pain Both predictor and descriptive variables

    Best Application Understanding phenomena Extrapolation of past and current events into uncertain or future predictions Understanding personal outcomes such as feelings, opinions, and others Big data analytics essential in making an informed recommendation

    Expected Findings More understanding of the phenomena that has already occurred or is occurring Forecasts of what is to happen An understanding of personal outcomes Recommendations for courses of action

  • freeCodeCamp.org
    November 16, 2020

    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!

  • freeCodeCamp.org
    November 16, 2020

    Thank you so much Max. Never stop what you are doing.

  • freeCodeCamp.org
    November 16, 2020

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

  • freeCodeCamp.org
    November 16, 2020

    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??

  • freeCodeCamp.org
    November 16, 2020

    Should I go to school for computer science. Will that help me get my foot in the door in becoming a Data Scientist?

  • freeCodeCamp.org
    November 16, 2020

    Good. Video

  • freeCodeCamp.org
    November 16, 2020

    Very general data science intro. But it's good cuz it's not too intimidating. More examples would have been better. More guidance in terms of other free resources would have also been good. But this video is good for beginners to understand statistics behind it.

  • freeCodeCamp.org
    November 16, 2020

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

  • freeCodeCamp.org
    November 16, 2020

    I didn't understand the part where @48:20 correlation doesn't imply causation. Well, of course it implies causation. If I drink coffee I feel better. This is because of the coffee. Or isn't it?? Please answer. Thank you.

  • freeCodeCamp.org
    November 16, 2020

    Hi Max, This is great stuff for any beginner in data science. Do you have any videos/tips on probability and logistic regression that are easy to understand as well? thanks!

  • freeCodeCamp.org
    November 16, 2020

    I need subtitles 😭😭

  • freeCodeCamp.org
    November 16, 2020

    Thank you!!!

  • freeCodeCamp.org
    November 16, 2020

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

  • freeCodeCamp.org
    November 16, 2020

    13:30 Hold up! Hold up! Does negative and positive infinity exist???

  • freeCodeCamp.org
    November 16, 2020

    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?

  • freeCodeCamp.org
    November 16, 2020
  • freeCodeCamp.org
    November 16, 2020

    Thank you!

  • freeCodeCamp.org
    November 16, 2020

    How can I become a data scientist with no programming experience? What are the steps shall I follow to become one? Thanks

  • freeCodeCamp.org
    November 16, 2020

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

  • freeCodeCamp.org
    November 16, 2020

    Hi Max ,thank you for your tips. Mima can understand that.

  • freeCodeCamp.org
    November 16, 2020

    Hello,
    I want to learn more about MI and I don´t know where to start. I just watched some math videos but it became boring over time just to do the math (I am not bad at math and atm I am studying IT-Security so I am familiar with "University Math"). This Video was great but it covers just a small piece of what I want to learn. Maybe someone have far-reaching videos that one can recommend? Thank you ;D

  • freeCodeCamp.org
    November 16, 2020

    From the course, it seemed that you are more like from Data Visualization rather than Data Scientist. You didn't talk about Probability distribution or Hypothesis Testing which are basics things for basic Algorithm like Linear Regression, and the second thing box plot is used to plot single variable to check how the values are spread out. We can plot single variable like Salary in box and Whisker plot. Data Scientist is much more than just visualization.

  • freeCodeCamp.org
    November 16, 2020

    I have experience in us recruitment and bpo and i wan to be s data scientist… how can i become data scientist in next 6 months.

  • freeCodeCamp.org
    November 16, 2020

    Thanks for the upload and for the timestamps.

  • freeCodeCamp.org
    November 16, 2020

    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.

  • freeCodeCamp.org
    November 16, 2020

    Physics student here also!
    I didn't know about the libraries, I'll give them a try in my next lab session 🙂

  • freeCodeCamp.org
    November 16, 2020

    now, make an advance level.. this is so basic…not enought to land a job

  • freeCodeCamp.org
    November 16, 2020

    plz , make more videos like these

  • freeCodeCamp.org
    November 16, 2020

    Thanks for all the great work you folks do.

  • freeCodeCamp.org
    November 16, 2020

    I'm about to finish my bachelor's in data science and this has been really useful to piece all my knowledge together. Thank you

  • freeCodeCamp.org
    November 16, 2020

    please upload tableau full course

  • freeCodeCamp.org
    November 16, 2020

    please make complete course on laravel 5.8

  • freeCodeCamp.org
    November 16, 2020

    ⭐️ 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

  • freeCodeCamp.org
    November 16, 2020

    No, you are not first, nobody cares. |:<

  • freeCodeCamp.org
    November 16, 2020

    😃❤

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