Staying Motivated in Data Science
Key Takeaways
The video discusses a tactic for staying motivated in data science by breaking down larger goals into smaller achievable tasks, focusing on one task at a time, and celebrating small victories along the way, as demonstrated by the speaker's personal experience and the example of Navy Seal Marcus Luttrell's survival story.
Full Transcript
learning and progressing in data science can be a humbling experience at times i was recently working with a friend on a data analysis project for a paper he was trying to publish previously to collect data he was going to websites and manually trying to capture accounts of certain keywords for his analysis as i knew this analysis could be automated with python i volunteered to help him out by scraping the data and performing the analyses my portion of the project was going great initially i had a solid plan of attack and multiple tasks along the way to achieve my final goal things were going exceptionally smooth as i was about halfway done and had built an initial script to scrape the data needed and was moving into actually cleaning up the data this is the point that i started to run into issue after issue and finally got to one problem that stopped my progress altogether as i'm sure you've encompassed in projects negative thoughts start to creep into one's mind like there's too much work left i will never finish this this goal is unachievable so how did i get through this low point in the project what up dad nerds i'm luke a data analyst and my channel is all about tech skills for data science in prior my life in data science i served in the military and during that time i picked up a pretty helpful tactic that i utilize in accomplishing and staying motivated with achieving my goals and my tasks even in my current role as a data analyst and with this project that i was talking about previously as i'll go to show i continue to employ this tactic in order to maintain a positive mental outlook when trying to conquer any goal so let's jump right into this tactic by going back to my time in the military and actually looking at how we applied this one tactic as a team for a large scale project during this time in my life my teammates and i would have very detailed and precise missions that we needed to complete i was stationed to a submarine where we would routinely have to deploy to a part of the world to perform certain tasks and then return home safely the overall mission would be broken up into a bunch of other major tasks itself so we had a task for actually preparing for the mission then we have another task for actually getting the ship away from the pier and then maybe another task to get to a certain point in the ocean now each one of these major tasks themselves were then even further divided down into smaller mini tasks with people assigned different responsibilities so overall this is the tactic i break my larger goals into small achievable tasks that i know i can accomplish from there i focus my efforts solely on these tasks and i don't focus on the larger goal at hand and along the way as i'm achieving these tasks i have many celebrations and those many celebrations help reinforce that that major goal at hand is accomplishable so the example that i just gave is being applied in a large scale let's look at this being applied in a smaller scale limited to an individual i feel a great example of this is that of marcus luttrell and navy seal that was captured in his book and also award-winning movie lone survivor not to go into all the gory details but the one event that really stands out to me is that of when marcus is abandoned and alone and he's badly injured in order to get help and also escape danger he has to crawl many many miles to get help instead of thinking of the major task at hand of having to travel miles upon miles instead he breaks it down into small achievable tasks he would set goals of aiming to crawl to a certain object that was within sight from there he would actually crawl to that object once he made it to that object he'd celebrate that small victory and then he would just continue to repeat this he continued this process for over seven miles and eventually made it to a location to receive help which ultimately led to his survival so you're probably saying luke how can you compare what that navy seal went through to what i'm going through in my journey in data science and quite simply the negative thoughts that you're feeling with when you're going through data science are the same negative thoughts that marcus was feeling as he was trying to make it through his survival and the tactics that he used i feel can also be used and what i've used in my life to achieve my goals so how does one apply these concepts in data science so let's give the example that you're trying to learn data science you want to become a data analyst and so you start looking at all the different tools you're going to need to learn in order to land your job it can be overwhelming at first because you're going to see like oh i need to learn spreadsheets so i have google sheets in excel oh i need to learn visualization tools such as power bi and tableau well there's also programming languages such as python and r there's also different databases such as mysql and postgres and and the list goes on and this alone is just overwhelming to think about all the different tools you can learn about so instead let's focus smaller and for example we would let's break it down even further and let's say we want to just learn one tool first well let's go with python with python we would then also break it down into even smaller tasks to learn so let's say i would start with learning variables next i would move on to functions then classes and then maybe onto packages that i want to implement with python as you start to learn each one of these small mini tasks i would go about maybe implementing it within some sort of portfolio project to therefore have that small victory if you will of actually implementing and utilizing what you just learned so whatever happened with that project that i mentioned the beginning of the video where i was stuck well embarrassing enough i did find the issue eventually and it was pretty simple actually python itself is case sensitive and i accidentally mistyped one of the variables with capital letter where it didn't need to be so the main point of this is i was able to overcome this obstacle that i thought was just detrimental by implementing those tactics that i talked about previously mainly i had that built up motivation from my previously achieved small tasks and additionally i was not focusing on the project as a whole but instead just focusing on achieving the next task on hand so i hope this helps provide you with a helpful tactic that you can utilize in your data science journey i promise you you are not alone whenever you have these negative thoughts or you have these set packs during the journey but you need to have some sort of plan of attack in order to overcome these obstacles and to continue to progress in this field as always if you got value out of this video smash that like button and with that i'll see you in the next one
Original Description
👨🏼💻 My FREE Course to be a Data Analyst 👉 https://lukebarousse.com/5daycourse
Ever feel like your data science goals are unachievable. Here is my tactic for dealing with failure and pushing through to succeed in your data science journey.
Certificates & Courses
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Coursera Courses:
📜 Google Data Analytics Certificate (START HERE) 👉🏼 https://lukeb.co/GoogleCert
💿 SQL for Data Science 👉🏼 https://lukeb.co/SQLdataScience
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🐍 Data Analyst w/ Python 👉🏼 https://lukeb.co/PythonAnalystDataCamp
DataCamp Subscription (Monthly $25USD) 👉🏼 https://lukeb.co/DataCampSub
Recommended Books
(Includes Amazon Affiliate Links)
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📚 All Book Recommendations 👉🏼 https://kit.co/lukebarousse/book-recommendations
📗 Data Science Must Read 👉🏼 https://geni.us/StorytellingWithData
📙 Tableau 👉🏼 https://geni.us/tableau
📘 Power BI👉🏼 https://geni.us/powerbi
📕 Python 👉🏼 https://geni.us/pythontricks
Tech for Data Science
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==================================
💻 Dell New XPS 13 (PC of choice) 👉🏼 https://geni.us/DellNewXPS13
💻 Dell New XPS 15 👉🏼 https://geni.us/DellNewXPS15
👨🏼💻 M1 Macbook Air 8GB (Mac of choice) 👉🏼 https://geni.us/M1macAir8GB
👨🏼💻 M1 Macbook Pro 8GB 👉🏼 https://geni.us/M1macPro8GB
🔌 Must-have Mac dock 👉🏼 https://geni.us/CalDigitTS3
🖥 M1 Multiple monitor adapter 👉
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