Hello Everyone, ive ben offered the responsibility to introduce Ai to a furniture company while i don’t have the skills yet… how/where do i start my learning from as to be able to land this in 6months as i’ve only got that long. I really want to thank everyone for donating their personal time to Guide not just me but every other learner.
Begin with the end in mind. Are you hoping to just introduce new ideas and possibilities? Are you planning to build and demonstrate an AI-based solution? What part of the furniture business are you hoping to impact? Customer demographics? Manufacturing? Design? Supply Chain? Forestry? I can imagine machine learning applications bringing insight and improvements in any and all areas, so you need to pick one and work towards that specific objective. I’ll go out on a limb and suggest that 6 months is a very aggressive time frame to learn about AI from scratch, acquire data, build and train models, and impact/transform a business. Very aggressive. In my experience big successes generally started with small successes, so be realistic about scope initially.
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@ai_curious This is Good informations and i hope theres a way to break down my learning process as im truly struglling with where to start as not to lose sight of what im really trying to archive. id like to know what course to start with i’m up for jumping between courses. all my time and energy can be donated into learning for the next 6 months and i need to start a project so i can make sense of most the things i learn
Hoping some of the mentors will join in here, but my suggestion would be to start with the Machine Learning Specialization. It introduces some foundational principles and techniques upon which much other material in ML and AI build.
I encourage you to think about the usage as soon as possible (maybe today you don’t know what you don’t know). The data and techniques for improving customer segmentation and marketing are different than those used in manufacturing quality assurance or supply chain management. So constantly think about and question how the course content can be applied to your objectives. This will help ensure you optimize your time. For example, maybe computer vision is very important, or maybe it is irrelevant and you shouldn’t invest time learning about it. I sense that finishing classes or getting a certificate isn’t your priority, so be laser focused on what moves you forward even if it isn’t in a single syllabus.
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First you absolutely have to define for yourself exactly what that statement means.
AI is a huge topic. You can’t learn everything in six months. You’re going to have to pick some short-term goal that you can reach.
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@kendrick-- I’m going to assume something stupid here, but I presume you already know alot about furniture (i.e. how it is designed, made, manufactured, warehouse, marketed, sold, etc)-- Yes ?
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@Nevermnd It’s not a stupid assumpting and I am a Structural Ananlyst, got no history with AI or relatives. the comapany has got no IT specialist as the owner don’t think he needs em yet and that’s where the idea came and wants me to comeback in 6 months with something to offer and he’s not expecting me to be an expert all of a sudden but equipped enough to get paid. i think learning and practicing will boost my growth and i want to started some kinda prject but still got no clue where to start.
@TMosh Thanks for your response and to answer that question i honestly think i need a mentor or tutor to navigate what i learn as @ai_curious mentioned. i hope i’m grdually making sense about my predicament
@ai_curious Thanks for your time and update. i just checked out the course and i do not meet the reqired skill to start ( * Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML). this is why i want to be careful where i start as my growth begins there
@Kendrick well, I think others got my point here-- it is one thing to be a ‘subject matter expert’ and not know anything about AI and have to learn that.
There, you already know your data and will have a good intuition about which models might best apply to your data.
On the other hand, maybe you know ML / AI really well, but have to learn about the subject-- At least there you already know this swiss army knife of models to work with, which might best fit the data as your learn some nuances, and know how to interpret the results (including knowing when it is time to go ‘back to the drawing board’).
However, IMHO, not being well versed in either would be extremely hard-- One of the greatest risks of trying to learn both at the same time is one might ‘miss the forest for the trees’-- Or see a model that looks like it could be nice, but not understand your data enough to be able to see ahead of time other models would be more appropriate.
On the other hand, you might see what you feel are apparent in the data-- but totally against business practices, or the practicalities of production.
Finally, in the end, since this is for work: 1) ML/AI, despite all the hype, is not a magic bullet. Even where it can make improvements, does the employer have realistic expectations (and can you meet them ?) 2) The employer is likely not an ‘AI geek’. They won’t care whether by four more months work you can improve accuracy by 0.2%-- or even overall accuracy at all.
All they will care about is can/are you making us money ?
So, just some advice.
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@Nevermnd Solid point made clear and i got it.
I need the education and growth more than anything and he gave me great reason to start now.
Learning about AI and data science now is another of exposing my Knowledge and figuring how i can use that as an advantage to worth more everyday than the last day. I choose this direction now cause i mean it’s (now) always the best time to start learning anything and it’s better knowing there are communities like this that makes it easy to understand whatever you’re learning, I’m Solid.
Say i’m not making enough money for the company and they’d have to let me go, that’ll sting but applying for another job or starting something of my own would be less troublesome as it should be cause i’d have taking the time working for them to elevate myself as much as i can.
Point being i’m here to learn not to fail early and that’s why i need guidiance on how to start and what ways i can practice what i’m learning. I know for a fact it is not impossible.
@Nevermnd , @TMosh , @ai_curious – How would either of you start learning to be useful enough to get employed by them in 6 months. The rest can only be progress from there.
''Someone told me to hire an IT team"
@Kendrick P.s. the advice about ‘making enough money for the company’ comes directly from Chip Huyen’s excellent text: Designing Machine Learning Systems[Book]
A lot of good advice in there about the ‘practical’ (rather than theoretical) side of ML in the real world.
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Many things I learned during my career in IT didn’t age well. Learning to program Mac low level stuff in Pascal is particularly not useful to me these days. One thing that really stuck with me though, was an opportunity I had through IBM to spend several days with a former CEO of a €600 million annual sales business. He told me he looked every morning at a small set of graphs on a dashboard. He used those to measure success, identify risk, and decide where to target resources deployment to in effect ‘bend’ those curves. Performance improvement in specific key measures of his business was the end. From there, he and his colleagues would decide on specific means they thought would be effective to achieve them.
If the furniture company doesn’t currently have an IT department it might not be using data to measure and manage the business. If you think about an analytics maturity model, effectively leveraging AI is pretty mature. It might make more sense to start with some more basic data collection and descriptive analytics. What is Cost of Goods Sold, Compound Annual Growth Rate, Effective Return on Capital, Order Time To Fulfillment, Etc … and what are their trends over time?
AI is one means to achieve one end. But that might not be the business goal that makes the most immediate impact, and might not be the most effective means to deploy to get there.
In the absence of any other information than in what is in this thread, I think learning how to put up a useful business analytics dashboard using easily accessible low tech tools like Excel might be a way to a 6 month win for you and the company and start you both on the business analytics maturation journey.
Cheers
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@ai_curious shoudda learned COBALT 
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Hello @TMosh @Nevermnd @ai_curious … hope all has been well with everyone
I wanna use this medium to thank everyone for their insights in various ways that helped me a lot.
With the data i skimmed from y’all, i’ve summoned the courage to speak with the overseer and explain possible tasks and impossible expectations which sparked a massive conversation of which i made most points clear to avoid disappointement on both ends.
We concluded that moving into the IT field would take too much time for me to be even the least useful and it’d be better i go for more realistic roles. Long story short he opt for a better role to assist both his machendiser and marketer(optional).
Good news though i’ve completed into python, ai for everone and also Learning How to Learn: Powerful mental tools to help you master tough subjects.
I’m ooking to build a project/product that’ll guarantee y private role in the company as there’s a possibility what i might bring to the tabke might be taking away and i’m trying to be careful as well be consistent to my learning and building some of great quality.
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@Kendrick I hope you know as well our intention was for you to be inspired, but at least also for myself, just make sure you didn’t get ‘in over your head’, as that could be very frustrating.
Keep learning, keep trying.
Thanks for the update. I admire your approach and initiative. Data and analytics can help your company make better decisions through understanding :
- what is happening currently and happened in the past (Descriptive analytics)
- what a next best action should be (Prescriptive Analytics)
- what might happen in the future (Predictive Analytics)
All these depend on clean, organized, and well understood data, which is often the first step in the journey. Be sure to look for free resources that can assist your learning growth. For example, here’s a page from Microsoft that has information about business analytics for sales:
The how-to part is Microsoft tool specific, but the ideas are not.
Boa viagem!
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