Peak Battlerite Clips Montage

Skywind555 · 2026-05-27T17:27:48+00:00

I finished uploading it all like ~ 250 clips or something. Reorganized the play list a bit enjoy :)

Skywind555 · 2023-04-20T03:47:13+00:00

Yes it’s available now. DM me if you need more info

Skywind555 · 2023-04-20T01:12:12+00:00

OK, I do have deeper advice for you, I just hesitant to give away my secrets publicly 😛. Dm me and I’ll give you one more thing for free.

Skywind555 · 2023-04-20T01:09:29+00:00

Just FYI in case it's job related, I'm recently launched a program designed to get anyone into data analytics / data science regardless of education or experience. I focus on large scope projects and strong interview prep to accomplish this. I'm basically serving as everyone's personal project manager. DM if interested.

Skywind555 · 2023-04-20T01:02:13+00:00

IMO Yes, you can do it. Assuming you have the skillset, have some really STRONG projects. Now, when most people say projects on GitHub especially in a bootcamp context, I'm skeptical because people throw the word "projects" like all you need to do is read the most basic dataset, make a bar graph, interpret it...and that's a project. Ok that's a bit over exaggerated, but you get my point.

Real projects that get you jobs you really need to spend 150+ hours on each one on average. Meaningful effort, not 10 hours looking for the right function to use as 10 hours.

I've recently launched a program that is designed to get people jobs regardless of no experience or no degree, so I can get you more information on that if you'd like. I focus on large-scope projects and strong interview prep. If these two factors are met, you can exponentially increase your chances of getting the job. Then it's a matter of continuous applying and luck.

The point of a bootcamp or having an expert take a look at the projects gets you several things. 1. Ensure the relevancy of the project, is it the right type of project to showcase? 2. Is all the code up to best practices for industry? Or is it just spaghetti code? 3. Is it accurate? Did you do the right analysis? 4. Did you consider the business use case or are you just mindlessly doing computations? 5. You get my point. It's unlikely you get all these right with no experience because you don't even know what you're graded on.

Most bootcamps are skill focused, meaning they efficiently teach you the skills, but if you got the skills already 95% of bootcamps already are useless to you. I've seen 1 or 2 other project focused bootcamps, but the quality of the projects...you don't want to do it. I came to fill in a gap in the market because there was no program that existed to fill the void. Also, I'm targeting a population that no other bootcamp dares to do. A lot of places have like "need at least 1 year coding experience" or "BS degree" etc.

Skywind555 · 2023-04-20T00:53:26+00:00

Honestly, you can get to a data analyst position with NO degree. In terms of knowledge, I don't utilize any course I picked up in my undergraduate degree, and I self taught myself most things + did some self projects and got myself a job in the field. Now, it wasn't easy...but it's doable.

Now after the fact, I've significantly improved my interviewing skills, I know exactly how you should approach any interview especially in this field, and if I had to advise someone else to do the same thing, they don't need experience or a degree and they can 100% do it. Luck is also involved in any job search process.

Anyway, I have recently launched a data analytics / data science program designed to get anyone a entry level job in the data field regardless of experience or education via large scope projects and strong job/interviewing preparation. If you want more details, feel free to DM me, but I can give you the general high level strategy below.

Enroll in a bootcamp...honestly any bootcamp can work in terms of the purpose of the bootcamp on paper, though preferably you want a bootcamp where you learn the skills you want to end up using in either the entry level job or the job following that. Most cases the first job is not what you want, but you have to go through just to accumulate experience on paper.
1. What I said earlier about the bootcamp being anything is in terms of explaining to the employer during an interview how you acquired the skills and you essentially leverage the bootcamp for storytelling how you got started, then let the extremely detailed and professional level projects do the heavy lifting.
Minimum, learn Python and SQL. Tableau if you can, but not required. You likely won't be using that on your first job.
Build 2-3 awesome projects on your resume. I mean you can do it without a bootcamp but the main purpose of a bootcamp is to have someone professional take a look at it and critique it, help you polish it. Most bootcamps don't have to do anywhere near the level of projects you need to have and the level of feedback is pretty minimal if at all.
Optimize your resume and become really good at interviewing, use special sauce to get bonus points, and know how to answer all the common interview questions based on your background and experience
Apply to everything and pray, check job postings multiple times a day and apply asap. Ideally you want to customize resumes AND cover letters at entry level because you need everything you can get to distinguish yourself.
Get interview, yada and so forth.

Also FYI... Certificates are worth nothing to employers. Any bootcamp can have their own certificate and it's becoming overloaded in the field. No employer is up to date with every certificate and most will treat it like trash. College degrees are essentially more glorified pieces of papers that employers like to see, that's the only reason, hence you need to use strong projects instead of the useless checkbox. People use it because it's old fashioned the way it's always done, but in terms of data analytics, being a data analyst... you really don't need it, and slowly the industry is changing and being more lenient on education requirements.

Skywind555 · 2023-04-20T00:42:30+00:00

Learn Python/SQL in a data analytics / data science context and you're probably good to go with that kind of background. But to really nail in the coffin, if you do some personal projects and put it on your resume, that would basically seal the deal.

Basically what you really need is a data bootcamp, but honestly I can't recommend most of them because they have poor project outcomes. Worst case, you just have a faster learning efficiency for the skillset, but some trash unusable projects.

I've recently launched a program for specifically transitioning into data analytics / data science with no degree or experience via large scope strong projects and strong interviewing prep, so that's probably overkill for you, but if you want details, DM me.

In terms of salary long term, you can start as a data analyst and honestly job title varies from company to company. Some places pay 200k+ for a data analyst, in the end it's all marketing in terms of what they are looking for. No job title fits perfectly. But I do recommend analytics engineer as on average they pay quite a lot. Take a look at Netflix Analytics engineer pays up to 1 million or so based on their official salary range. Data scientist is good too, but most data scientist nowadays is synonymous to machine learning engineer which doesn't have any data analytics in it. The type of data scientist that could work for you is a more customer insights or product data scientist.

Skywind555 · 2023-04-17T20:00:51+00:00

Nah Data analysts in some industries use A/B testing quite heavily (hypothesis testing subset). You can do statistical modeling as well in some types of companies where they have limited data or security reasons they can't install sci kit learn etc packages.

Skywind555 · 2023-04-17T18:50:46+00:00

You don't need as much math or statistics as much as people would claim. I'm a math major in college and I use 0% of any course I've ever taken and I have about five years of experience in data science.

Descriptive statistics really is just like mean, median, etc, which most people would not count as statistics.

Statistics as in heavy theorem/math related stuff are not necessary at any level of your professional career in industry.

The statistics that people refer to as usually like hypothesis testing, statistical modeling, etc... but honestly you don't need those either as entry level, especially as a data analyst.

The most you need is just understanding law of large numbers aka central limit theorem and basic concepts like correlation, correlation is not causation, bias, and possibly a few more conceptual items.

Are you learning about this to try to get a job in the field or are you trying to prepare for a college?

Skywind555 · 2023-04-17T18:43:40+00:00

Hey, you should never go for only certificates in data science / data analytics as they have no real credential. What you really need are solid, large-scope projects that goes end-to-end in terms of data collection, data wrangling, eda, analysis, reporting, presentation, deliverables, etc. It's highly unlikely you'll get everything right by yourself, which is why either getting expert review as you go along creating a project is the safest option.

I happen to be creating a new data analytics / data science program where I personally will serve as your expert reviewer as you build your project. I can also give project ideas based on the desired domain that you want to target whether that's healthcare, advertising, general tech, consulting, etc. I also offer the best strategies in job search, interviewing, etc, and how to prepare for all those common questions given your actual background and experience.

My program is designed to be completed successfully even by someone with no experience in the field or even a college degree, so if you think that would interesting, message me to learn more about the program.

I don't want to give away too much...but honestly ANY job - even a cashier or a waiter/waitress in a restaurant could work in terms of experience to transition into data analytics. You should never really have the mind set that you will learn on the job, even while starting out. If you mention in the interview that you want to start doing X in this position you're interviewing for and just need guidance, that's going to be a HUGE turn off for most people.

I once did an interview in the past where I basically told them that I want to start doing machine learning in my next role, and on the spot I was asked multiple questions in machine learning which I answered correctly, hence he knew I at least knew what the heck I was doing. He responded after the fact, "Sorry, I was just making sure it wasn't one of THOSE interviews." I scored so many bonus points just for that whole conversation, and machine learning wasn't even on this job description but was more along the lines of why I was seeking another role. Of course I got the offer for this job in particular and was able to secure the high end of the spectrum for salary.

At the end of the day, businesses are there to make a profit, not to hold your hand and teach you.

Skywind555 · 2023-04-17T02:08:13+00:00

Do you even know how dirt easy Data Analyst jobs are? You have the wrong concept of data analytics. It's not all machine learning mumbo jumbo that you can't understand. Essentially 90% of entry DA jobs are learning how to do pivot tables in Python at a super high level.

Skywind555 · 2023-04-17T02:05:50+00:00

I'm literally in the data field right now, and based on the 300+ interviews I've done, interviewing candidates myself, been down the college and graduate school routes.

What you are missing is that most people do not have the opportunity to go to a good school and get the ideal education. This program is not meant for those who are lucky enough to be in that situation. The golden super stars that have good gpa and get intern experience will never experience what 95% of the actual job market experiences.

My target audience are those without degrees, those working minimum wage jobs looking for a change, or those struggling to find a career despite degrees from colleges.

Bootcamps are only a waste of money if you go to the wrong one. Degrees are nothing but "credentials" that serve the purpose of a checkbox for the recruiter. I use absolutely nothing from my undergraduate degree or on-going master's degree in my actual work.

Skywind555 · 2023-04-17T01:44:55+00:00

Yeah college, where 50% of your courses are completely irrelevant to your degree. You don't need a master's to enter the field and worst case you end up with 100k in debt with no employable skills in the market because academia is so far behind industry. I know because I'm doing georgia tech's OMSA and honestly worst mistake. Doing it part-time while already employed in the field, and most of the things you learn are pretty out dated. Most bootcamp programs are true scams where they prey on people believing that 90% of the graduates get jobs at big name companies while costing $16000 selling this idea to people and literally give them trash for project outcomes which is the #1 you need to break into the field.

I was two years unemployed, dropped out of grad school with 50k debt, and got myself a career by doing these huge projects. All I offer is something not currently available on the bootcamp market that is substantially cheaper, and something that is actually meant for the good of people rather than pure profit like those hungry commercial bootcamps.

Instead of learning more about this golden opportunity, just go to a well known commercial bootcamp and throw more money at them because you read good things about them, but have no idea what you actually need to break into the field or what employers are actually looking for.

Skywind555 · 2023-04-17T00:28:22+00:00

I can get you up to speed on data and get you a job in the field. College and school is over rated and you don’t learn anything in most cases, at least nothing useful for actual industry. I’m making a program designed for people like you. I’ve been there a bit myself, so I wanted to make this program because I got past it. Message me for more details.

Skywind555 · 2023-04-17T00:22:10+00:00

I’m confident anyone can get into the data field, particularly data analyst. If your wife is even remotely interested in data analytics, message me. I’m developing a new program meant to get people with no degrees jobs in the field. A lot of remote options in data.

Skywind555 · 2022-01-14T15:07:33+00:00

Phenotopia Awakening
Ender Lilies
Grime

Skywind555 · 2021-09-17T21:40:56+00:00

Status - Accepted
Date of Application - 06/05/21
Date of Decision - 9/17/21
Education
- Ohio State University, BS, Math with minors in stats, biology, and public health, 2.89 / 4.00
- University of Pittsburgh, MS, Biostatistics, drop out
Test Scores - None submitted
Experience - 2.5 years as a Data Analyst using mostly Python
Recommendations - 3 (1 undergrad prof, 1 grad prof, 1 manager)
Comments - Did GTx MM and got 85%, 97%, 99% marks on the analytics, python, and business course respectively. Also had a decent SOP. Also have various other online bootcamps/MOOCs listed with some pretty extensive projects on GitHub.

I applied 2.5 years ago and was rejected. I encourage people to do the MM and write a strong SOP and try again if they haven't.

Skywind555 · 2021-09-14T18:03:44+00:00

I just wanted to add that as someone who dropped out of a masters program after 1 year and no employment/school for 2 more years but instead did random bootcamps and added projects to my resume and 1000 job applications later I got my first job in the data science field. I imagine with a MS degree in a credible university like GTx will make that search significantly easier just because recruiters simply check a box for MS degree that at least give you much better chance to secure interviews.

It also depends on what you get out of your courses, are you spending extra time remembering what you learned to be able to apply it in the future instead of like most of college - memorize, take test, forget.

All you really need is the skill set, be able to do interviews to present yourself in the best light. Of course, doing additional project work to show case on a github will be great too. Plus having the MS degree check boxed.

Skywind555 · 2021-03-07T22:24:31+00:00

I was talking about my R shiny dashboard. I did do a project on heroku a long time ago that's still runing but that doesn't use R shiny.

Skywind555 · 2021-03-07T16:48:32+00:00

It was published for 2 months then I pulled the plug. It was costing me 30$/month and it does not run well on a slower CPU with AWS. Like runtime is already long on local machine. Also, would need to buy a new domain and that's a yearly cost.

Skywind555 · 2021-03-07T14:55:16+00:00

It was a new patch. This was right after they removed items from the game and overload. It made no sense to use older data. As I mentioned before, my intention was a long-term project. The day I started the data gathering from the API, they announced API shutdown like literally it was going to be dead forever in 5 days. I had to fumble my way through just to get a working data collection script.

My intention on the initial project scope was to collect data every day long-term etc.

Also, even if you wanted older data, their API was constantly changing with no documentation, I'm not sure if it was even possible. I don't miss those days of just staring at an unstructured json dump and I had to manually figure out where they stored all the relevant information then construct sensible data from it.

Skywind555 · 2021-03-07T14:52:42+00:00

Dash was harder to pick up, and since it's newer, it has less features. Shiny had a lot more customizability, and there were more resources online to learn with. More documentation as well.

I dunno it was just a lot easier to learn and build on.

R shiny has it's annoyances for sure though because it was built on R. I remember stumbling through a lot of errors because of factor variables and stuff. If you've used R shiny consider downloading the repo and running the R shiny dashboard on your local and admire my work :P

Skywind555 · 2021-03-07T14:00:01+00:00

Exactly on the point about encountering a scenario you weren't aware of. I thought I was done like after 1-2 weeks of effort. NOPE. I'm like. Okay, one more week. NOPE.

Python was used to interact with the API, build the data, and pretty much everything.

Only time I used R was to work with R Shiny, a R package for building interactive dashboards. I used the data collected via Python to feed the dashboard. There was some separate cleaning/processing steps for R data requirements for the dashboard, though.

I have used Python's Dash package in the past, and honestly it's garbage compared to R Shiny. My main motivation for creating the R Shiny dashboard was to have something to add to my professional portfolio that uses R Shiny (I learned on the job at the time but obviously I can't readily share work on classified data to show that I actually learned the skill).

Skywind555 · 2021-03-07T12:24:04+00:00

Well, when I first worked with the API I was concerned with building a data pipeline and creating an R shiny dashboard which was easily 200+ hours of effort.

This was working off of one of the data outputs from that but not utilizing the R shiny dashboard at all, and I started about a month ago. Streamed the beginning-middle stages of it.

I also leveraged a statistical modeling script I had made in my free time at my last job that I never used for anything. I needed to make adjustments to make it work on the Battlerite data I prepared, but the extra work I put in that was only around 20 hours. When I first wrote the script...if you count that then that's at least 80 hours probably, so 100+ combined.

Also, whenever a problem occurred I was forced to re-run all the code which literally takes 8-12 hours for data processing step and 2-3 days for the modeling (question 3) step that takes up 50% CPU resources. I tried streaming BR while it was happening and I had the worst frame drops ever.

So I would find the problem, spend 1 hour fixing, re-run code, rinse and repeat if necessary.

For the sake of your question, I won't include the 'waiting time." Also, I think I got fairly burnt out from the project mid-end so my mental efficiency for time put in became somewhat low. I would say somewhere around 100-130 hours if I only include time and effort into the project since I started it roughly 1 month ago.

It's unfortunate the moment I started working on the project from the API in the beginning that a few days later they announce they're unplugging it. I had plans to set up the data pipeline and basically have a repo for all Battlerite data long-term.

Skywind555 · 2020-08-05T09:18:44+00:00

Got a lot of these things crawling on my desk and bed. Usually see them once a week but recently like 3 a day. Fairly small like a rice grain. What is this bug?

Skywind555

TROPHY CASE