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This approach will help you think of a solid startup idea.It is broken into 5 steps to facilitate progress through a system that in total should take about 30-40 hours to complete over a week or two, if you do it all.Add rigor and discipline to your brainstorming and idea evaluation process:Build lists of potential customer types and business or pricing models.Evaluate the opportunities where these lists overlap.Then, exit your ivory tower and evaluate the top ideas with real potential users, customers, or suppliers.This will improve your likelihood of success and waste less time down the road, even if you pivot from your original idea.Preface: There certainly are simpler answers like, “pick an area that is trending”, “look for a large market that hasn’t changed in 10 years”, or “convert your hobby into a business”. Unfortunately those aren’t particularly helpful, and since this question comes up often in discussions, I wanted to get my thoughts down in a more comprehensive way. I’m sure Quora will have some good feedback for me :)Also, while this answer covers the ideation part of the journey, keep in mind that implementing the idea is the hard part.Three primary paths to a new business idea1. The spontaneous idea: It hits you when you’re in the shower, driving in your car, talking with friends, or doodling during a meeting. The dots suddenly connect in a new way and you have an epiphany...your sudden insight is surprising and exciting, and the value of this new idea seems obvious. You can’t believe nobody else has thought of it before!So you go online and poke around...and...most of the time it turns out that someone has thought of it before. But, you still might be able to do it better...so you keep thinking about it and a day passes, and you start to realize some problems. You share it with a few trusted friends and get feedback about a lot of things you hadn’t thought of yet (e.g., nobody pays for it, it’s a tiny market, etc.). It could turn out to be a great idea, but you don’t know, you have a good job, and it is uncharted territory...so you let the dream slowly die away. Cheer up, that was probably the right decision.2. The insider idea: Maybe you’ve spent the last 7 years building enterprise software for airlines and you’ve noticed some voids in the product stack or issues with how your company brings it to market. You point these deficiencies out to your bosses, but there are other company priorities and nothing changes. Or, say your company pays vendors a lot of money to do some work, but nobody ever seems happy with the results....and you see a way to do it better for less. Or, maybe you witnessed your company kill an amazing new product or feature not because testing didn’t show user interest, but for political or organizational reasons.You see an opportunity to do it on your own, so you start moonlighting on a solution. You gather more specific information, talk to trusted co-workers and industry contacts, and determine the viability of solving the problem. The good thing is, you’re already knowledgeable and well positioned/networked in the business space...so good luck to you!3. The deliberate idea: In this case, you aren’t starting with a business idea. Instead, you’re starting with a desire to create a new business and become an entrepreneur. You may be ready to quit your job and go for it whole-hog, or just start it on the side of your desk...but you’re looking for the right business idea to pursue (which could be a business related to your work environment or industry, as in #2).While the first two paths may happen unintentionally, the third is for people who know they want to start a company, but don't yet have their idea. If you fall into the third group, then this answer is for you.#3 The Deliberate IdeaIdeation is fun and freeing, but it is the easy part of the process. Execution of your idea separates the wheat from the chaff and is where most people fail. That said, coming up with the right idea will improve your odds of successful execution. This system will help you do that well.Step 1 - Decide what is your primary motivation or personal goal for starting this (1 hour)For example, do you want a:Fun or hobby based business (e.g., making bracelets to sell on Etsy (product))Part-time lifestyle business that could become full time (e.g., running a wine-investment club)Full-time startup hoping for acquisition exit in 3-5 years (e.g., It’s like Airbnb (product) for fish, get it?)Large, cash-flow positive business (e.g., B2B furniture import and delivery business)Path to industry credibility and networking over financial gain (e.g., scriptwriting peer-training exchange for aspiring comedy writers)Create a new spreadsheet and write down your goal in the first tab. It may seem like overkill now, but if you take a break from this project you’ll want to be able to have it as a frame of reference when picking it back up.Step 2 - Frame the problem (2 hours)If you try to just write down a list of ideas from scratch, you’ll probably be underwhelmed with the results. You’ll likely hit a block after a handful of ideas, and what you come up with will be based on your predispositions...i.e., if you are a gamer, you’ll have ideas for games. If you work in cloud computing, you’ll have ideas for new approaches, etc. This isn’t a bad thing, but it is limiting.Instead, make a deliberate effort to facilitate your own brainstorming.In the spreadsheet you created in step 1, create a new sheet and type out a list of 15-20 different categories of customer/audience types in the first column. Don’t start with the usual demographic descriptions like, “18-35 year olds in urban environments making over $100k per year”. Instead, use descriptive phrases that represent specific groups of consumers and/or businesses with unique challenges and needs. These tend to be easier to conceptualize so they are more useful and helpful for generating ideas.Start with some that relate to your personal interests, hobbies, experience or professional network, but don't limit yourself to them. Some examples include retail insurance agents, cyclical dieters, ex-pats in Asia, news junkies, people that eat out 3+ times per week, new college grads, stay-at-home mothers, winemakers, startup founders raising money, youth sports teams, companies at trade shows, wedding planners, gamers, health nuts, software development agencies, etc. If you’re having trouble coming up with enough, broaden to specific industries, e.g., public transportation, dating, real estate, etc. If you’re going after a specific geography, call it out (e.g., ex-pats in Asia).Next, along the first row of your spreadsheet, type the business or pricing models (i.e., the type of business) that you could apply to these customers/audiences. There’s no exact right or wrong approach, and I’m using the term “business model” very liberally here. Not all models will apply to each group and some overlap is okay. Remember, you’re doing this to help you brainstorm and compare new business ideas, not to become an expert on business models.For example, subscriptions, product bundling, risk management/insurance, auctions, resale/classifieds, peer-to-peer exchanges, outsourcing non-core functions, freemium, advertising-supported content, new product development, after-sale care, daily deals (discounted pre-sale), collaborative consumption (think AirBnB), rapid evaluation/matching (e.g., Tinder), sales channel innovation, lead generation and referrals, marketplace, brokerage, BI/CI solutions, community, etc. (more here: TechCrunch business models)Step 3 - Generate ideas (4-6 hours)Your spreadsheet is now a grid with customer/audience types down the side and business/pricing models across the top. Each box where the two lists overlap is a place to brainstorm ideas. Go through each square in this grid. You can dismiss many of the boxes in a few seconds (e.g., Business Intelligence for stay-at-home moms?), but it is worth giving each consideration as you’ll inevitably come up with ideas you didn’t expect.The easiest way to do this is go column by column. Pick a business or pricing model, think of a few existing businesses that use it, and spend 5 minutes reading about them to get your head into that space. Then, apply it to each potential customer or audience group: how could it fit? What are their priorities, what gets in their way, where are they wasting time or money, what do they depend upon? Browse discussion forums where they participate or are discussed. See what they care about, what people complain about. Search online for other companies that already compete to offer them products and services. What are they?Your pass through the first column will take the most time, because you're learning about each of the 15-20 customer types as you go. It speeds up after that.Each time you come up with a keeper, type it into the corresponding box. For example, providing after-sale customer management for retail insurance agents? Or, a debt auction business for startups looking to raise seed funding? Type it in.Note: You may have 2+ ideas in a box. To add a new line inside of a cell type Alt-Enter for Excel on PC, Option-Command-Enter for Excel on Mac, Ctrl-Enter for Google Docs on MacTry to come up with at least 6 solid ideas. Then, create another tab in your spreadsheet and list all of your ideas there. In addition to writing down the ideas themselves, you should state the goal, audience(s), and model(s) for each one. These will change over time, but it is good to start grounded with something you can work-back towards.Step 4 - Evaluate ideas and narrow it down (3 hours)The next step is to evaluate your list of 6+ ideas against a set of criteria that will help you narrow down to the most promising three. For example:Heat in this space: E.g., Some answers on QuoraYour experience and connections: Do you have experience in this industry or with similar businesses? Are you well connected with friends or family that operate in this space? Any advantages, or disadvantages?Alignment with goals: How well does this align to your original goal? Are the upfront capital costs compatible with the level of investment you want to make in this business?Market opportunity: How big is this market and how unique or differentiated is your approach? Consider competition here, but don’t be discouraged by the presence of competition. It is validation that the space is interesting. Also, there are plenty of companies have come along and disrupted markets that others had written off as already solved, like:Google ... after Altavista, Metacrawler, Lycos, etc.Facebook ... after Friendster, MySpaceUber ... after Yellow cab, black car services, etc.Gmail ... after AOL, Yahoo!, Hotmail, etc.iPhone ... after Blackberry, Palm, Windows MobileFlipboard, Wavii, Zite, Pulse, Prismatic, etc. ... after Yahoo!, AOL, MSN, CNNYou probably don’t have time to really deep-dive on 10 ideas, so getting this narrowed down is both science and art. What does your gut tell you, what would be fun, where are you most comfortable and confident?OPTIONAL STEP: To add more science try quantifying some of these criteria.To do this, add a column to the Ideas tab, one for each criterion. Then, for each new column score your ideas from 1-5, with 5 being the best. So, for “Alignment with my goal”, a 5 means it aligns perfectly, and a 1 means it doesn’t align at all (e.g., your goal is to create a fun hobby business, but the idea is to sell offshore development services to technology companies in the US).Don’t worry if you aren’t sure whether something is a 3 or a 4, just go with your gut or do 5 minutes of online research. Keep moving forward, don't get stuck here bogged down in the weeds.When you’re finished, add up the scores and sort your list by the sum of these scores. In theory, the higher the score, the more interesting the idea should be to you.When you’re done evaluating your ideas run them by a couple of trusted friends, and narrow it down to the three that seem most promising. If you do the optional scoring step, don’t feel like you must pick the three that scored highest.Note - we could have used these criteria earlier in step 2 to narrow down the list of audiences and business/pricing models, but that would have limited the creative process too far upstream (i.e., before the brainstorming process), so I suggest waiting.Step 5 - Deep dive on those 3 ideas (20-30 hours over a week or two)Congratulations, you have come up with 3 solid ideas! Now it’s time to step out of your ivory tower and start getting street-level information and feedback. There are three basic steps for doing this (i.e., 5_a, _b, and _c) that are general enough to apply to most types of ideas.A quick aside: at this point people ask, "If I share my idea with a lot of people, won't someone steal it?" The answer is possibly, but unlikely. As previously mentioned, there are a lot of startup ideas but few people with the time, energy, or know-how to implement them. The benefits of getting good feedback early on outweigh the risk that someone will steal it. So, don't tell people that won't benefit you, and avoid telling direct competitors that are in a position to do it themselves, or to block you from doing it, but generally don't worry. Related questions / blog posts:Will a VC or Angel steal my idea?How can I be sure people won't steal my idea during a pitch?Will anyone steal my startup idea?Why you shouldn’t keep your startup idea secret5_a. Get smart(er) (6-8 hours)You will be able to evaluate and refine your ideas 10x faster by engaging in discussions with real potential customers, users, and partners. But, if you go into these unprepared you’ll wind up asking the wrong questions, sounding out of place, and wasting your opportunity and their time.So, before you invest in surveys, coffee shop chats, or informational meetings, you need to get up to speed on the basics of the industry you are targeting. If you gave yourself a 5 in the “Experience and connections” category in Step 4, you can skip this. If not, invest 2-3 hours per idea.Note - throughout this process you should take detailed notes. Create a new tab for each of your ideas, or an entirely new document; doesn’t really matter as long as you can write stuff down. Track who you've spoken with, emailed, feedback, etc. Trust me, you will be glad that you wrote this all down.This will probably take a couple of days. At minimum I would:Call up or email savvy friends and family to get their thoughts (LinkedIn is a great tool for this).Give them the 10,000 foot view of your idea and ask for their opinion. (Take good notes on or right after the call; do not trust your memory for this.)Ask them what they think is the biggest problem with it, otherwise they might just say nice things.If they’re in your industry then ask if they know of other companies in your space, what they think is broken, etc.Ask them who they would speak with if they had your idea. Ask if you can get informational interviews with those people.Talk to potential investors if possibleThey don’t have to be the people that will actually invest in your business, but at this step ideally you have a personal relationship with them. Position your conversation as looking for advice to make a decision, not their money.Anyone you know that does angel investing, VC, M&A, etc., will have a trained perspective.Do lots of online research. For example:Find out who competes in this space, and add them to your spreadsheet.Read their websites, watch their videos, and search for them together, e.g., “Windows AND Android AND iPhone”. These search queries surface articles and blog posts that analyze the broader industry, offering helpful perspective and discovery of competitors you missed. E.g., “Windows, Android and iPhone versus Blackberry”.Browse on Wikipedia to learn industry vocabulary and organization.Search Quora for questions about the industry or these competitors.Determine external dependenciesYou may need data. Is it available free or paid, or will you have to mine it yourself, etc.?Do you need any particular physical materials, machinery, etc. that are hard to come by?Will you require any permits or government approvals?Will you need to hire any specialists people that are particularly difficult to find and recruit?Expensive equipment?Will you need to raise a significant amount of outside funding just to get started b/c there are high capital costs?Etc.Now you are smart enough to have the intelligent conversations with people in your prospective industries, and you probably have also improved and refined your ideas. Woohoo, you’re getting closer to “the one”.At this point a lot of people would pick something and invest time in “creating” their business. I.e., set up a corporation, pick a name, secure a domain, design a logo, print business cards, figure out their title, etc. While these things feel like progress towards a “real company”, they are an unnecessary distraction at this point. It is much wiser to spend that energy on validation of your idea, like testing with real customers, meeting competitors, mocking up prototypes, etc.5_b. Talk to potential customers, competitors, and industry partners you don’t know personally (5-10 hours)Before you pour your heart and soul into a new venture, you should validate it outside of your friends and family circle. Is this solving a real issue for potential users or customers? Would they be willing to pay for it...or do businesses even have budget for what you’re offering? Again, the mechanics of this depend on the type of business idea that you have (e.g., starting a sandwich shop vs. office supply delivery vs. peer-to-peer insurance), but here are some general approaches that I would recommend.Run an online surveyQuick way to get a relatively large sample of answers from your target customers or audience.There are probably others, but Google Surveys is drop-dead simple to use and it allows you to easily limit responses to your target (e.g., people that buy life insurance).It’ll cost you a couple hundred bucks per survey. A cheap alternative is to post the concept on a discussion forum or Quora to get feedback.Talk with your potential customers/audienceIf you’re targeting consumers, figure out where they spend time and go there to ask them questions (e.g., certain neighborhoods or coffee shops, concerts, sporting events, conventions, etc.). If you end up in a coffee shop, print a sign for the back of your laptop that says “Your feedback on my idea for a free latte”!If you’re targeting B2C businesses, approach them as a customer, and ask them some questions. Buy something if they sell retail.If you’re targeting B2B businesses, email them or go to conferences that they attend, etc. Try to get an informational interview based on the premise that you’re working to improve the industry and do something valuable for them, so you need their expertise and advice. People like it when others ask for their ‘expertise’.Talk with suppliersThis is relatively easy, since you are a potential buyer and they will want your business.In a previous step you identified the external dependencies you’ll want to take, i.e., what you should buy vs. build, and some possible vendors. Get meetings with them.You need to verify your assumptions, and while a lot of the details will be available on their website, information about pricing, access restrictions, etc., is often not, so you’ll want to email or call them to get details.Try to speak to more than 1 provider for each item so you can compare prices and look for differences or similarities, which will tell you a lot about the industry.OPTIONAL - Start selling before you have anything to sellSome people call this doing a “smokescreen test”, and the mechanics of it really depend on the business idea. In many cases, it actually won’t be practical to do this until you are working on your final idea.B2C: If you’re targeting consumers you can do this via the Google or Facebook ad platforms.B2B: If businesses, then send a bunch of emails to potential customers (you can find them online) with a proposed offer and price...vary the price and offer details and keep track of how people respond (hopefully some do). see if you can get on the phone with one or two of them. Learn what questions they ask, what they push back on, if the price seems reasonable. If someone wants what you’re selling, then you may have your first customer if you can deliver something quickly (you won’t be the first to sell something before you own it...remember Bill Gates and IBM (company))5_c. Write abbreviated business plans (7-10 hours)We’ve spent a lot of time working on the individual components of each idea, and now it is time to step back and see the big picture. Bring your thinking and research together into a brief business plan for each idea that still appears to be worth pursuing. If it is obvious from the previous steps that that an idea isn’t going to work, drop it.Here’s a suggested outline. Try to limit it to be 2-3 pages, and no more than 3 hours per idea:Page 1One-line description of your idea:[Company] will <do, make, or provide> for <target audience or customer> so that <the value/outcome you bring>.Example: Lewis Industries will develop customer management software for automotive dealerships so that they can increase loyalty post-sale and sell more services and upgrades to consumers that buy vehicles.Description of your products and services: 150 word description of the problems you are addressing and the scenarios you will focus on first.Page 2How and when you monetize: Will you start as a free service for everyone, and hope to monetize later through premium offerings (freemium) or advertising (ad-supported)? Or, will you start charging immediately, or never? You won’t know for sure, but give your best guess.Distribution model: How will potential customers or users discover you? What marketing and/or partner channels do you plan to use?External dependencies: For what core things will you rely on others to provide, e.g., A database of all vehicle makes and models, and option packages since 1970? You should have this list from previous steps, and don’t worry about generic things (e.g., office space).Page 3Estimated cost to reach your Minimum Viable Product (MVP): Just try to get in the ballpark here. The main reason to figure this out during the ideation stage is that it will impact how you approach starting the business, which may or may not align with your goals. I.e., if you’re planning to build a Zipcar for trucks and need to raise $2 million for the vehicles, then you probably can’t do it as a lifestyle business off the side of your desk.What are the major external dependencies and how much will they cost (e.g., $20,000 for the automotive database)How much development and design do you need to do for this idea, any large capital costs (e.g., a fleet of trucks)?Here are some places to learn how to estimate these costs: Estimating startup costs for a new businesses (StartupNation), How to estimate the cost of starting a business from scratch (United States SBA), Estimate startup costs (Entrepreneur)Summary of idea’s strengths and weaknesses (1-2 sentences for each)Research: What did you learn from your survey, calls, emails and online research that supports or challenges this idea? E.g., Positive if 67% of people surveyed say they will pay $10 for this, less so if 4 of the 5 companies you spoke with have no interest in what you’re proposing.Industry/macro trends: Will you have a tailwind or a headwind doing this? List out the specifics (e.g., My largest customer, retirees, is estimate to grow at 10% per year for the next 20 years.)Your knowledge and connections: You'll have a good sense for this, but write it down anyways. E.g., I have spent 4 years working on software for this industry, and x, y, and z from college are potential buyers.Risks: Are you taking dependencies where the solution isn’t yet clear? How competitive is the market, and what advantages do competitors have...or, is competition not a deterrent for x reason?You could easily increase the scope of this business plan by an order of magnitude, and there are a dozen templates for this (Writing a Business Plan) or approaches to analyzing your ideas (e.g., SWOT analysis). The important thing is that you’re being honest and self-critical, because ultimately you are the one taking the risk.Step 6 - Pick the best idea and get startedIf after all of this digging you are still feeling really good about one of these ideas, then go for it...this is where the real work begins. You’re going to need to think about financing, hiring, networking, and business operations in addition to the fun part of actually building your product or service.That is for another post! In the meantime, here are some resources to help you on your way:First I'd sit back and read...Startups are roller-coasters that often end in failure...make sure that you know what you're getting yourself into! Check out Mashable’s post on Why 90% of Startups Fail, David Lee's on Why I Never Started My Own Company, and Dave McClure's slides and video about “Why not to do a startup”.Now, if you still want to do this, read Paul Graham 's essay on How to start a startup (he also has an interesting view on startup ideas)Next, grab a drink and read Quora's take on what first timers often miss - What first time entrepreneurs are blind toThen, Jimmy Wales' answer to how to contact him about a startup idea...it applies broadly to how you should contact a potential advisor or investor about their startup.Lastly, go up-vote something Ashton Kutcher wrote on Quora and ask Mark Zuckerberg a question that he won't answer...Congrats! You're half-way to a great startup (scene story for your friends). :-)Startup advice and storiesQuora questions - What is the hardest part about staring a company, Common mistakes made when starting a tech company, Top five things to remember whens starting a companyJames Altucher, TechCrunch - Should you start a company?Jason Goldberg, Betashop - 13 things you must do every week as a startup CEOSeth Sternberg, Meebo co-founder (acquired by Google since this article) - From nothing to something. How to get there.Ben Horowitz vs Fred Wilson - Ben posts (case for fat startup), Fred rebuts (fat not healthy), Ben rebuts (revenge of fat guy)Neil Patel, Geekwire - Wish I would have known before starting my own businessDane Carlson - 20 things not to do before starting a business (I agree with most of this, but not #1 if you can afford it)Scott Weiss, TechCrunch - The path to starting a startupJames Altucher, TechCrunch - What you can learn from Woody AllenErick Schonfeld (2006), 5 ways to start a company (without quitting your day job)ChecklistsRyan Roberts, Startup Lawyer - If I launched a startup (great cheat sheet)Quora - How do you start a companyForbes - 38 things to do when starting a business (non-tech)Fiverr (marketplace) - Startup checklist (non-tech, and website is a little kitschy with all the dashes, stars, and arrows in the text)Finance and LegalQuora - What questions do entrepreneurs want to ask venture investors most but are afraid to askUser-10887637379381104900 - So you want to raise seed capitalFred Wilson, AVC - Financing options for startups, Financing options: convertible debt (likely way you will raise your first round of angel/seed money)Ryan Roberts, Startup Lawyer - How convertile debt works, What type of entity should I form, What does a series A term sheet look likeMartin Kleppmann - Valuation caps on convertible notes explained with graphsOrrick - Startup toolkitBrad Feld, Foundry Group (venture capital firm) - Term sheet series wrap upHiringBabak Nivi, Venture Hacks - What does an employee offer letter look like, Questions recruits might ask Part I, Part IIRobert Scoble, Quora - How to avoid hiring the wrong people for your startupElad Gil, Elad blog - Hiring for cultural fitBlogs by entrepreneurs:Jason Goldberg - BetashopDanielle Morrill - Danielle Morrill’s blogMarco Arment - Marco.orgBen Milne - Ben Milne’s blogKate Kendall - Kate Kendall’s blogGuy Kawasaki - How to change the worldSeth Godin - Seth Godin’s blogSriram Krishnan - Sriram Krishnan’s blogPenelope Trunk - Penelope Trunk’s blogScott Adams - Dilbert blogNeil Patel - Quick SproutEric Ries - Startup Lessons LearnedSteve Blank - Steve Blank’s blogDharmesh Shah - OnStartupsQuora - Other startup founder blogsBlogs by VCs:Brad Feld (Foundry Group) - FeldThoughtsFred Wilson (Union Square Ventures) - AVCDave McClure (500 Startups) - Master of 500 hatsPaul Graham (Y Combinator +) - Paul Graham EssaysDavid Lee (SV Angel) - dasleeUser-10887637379381104900 (Andreessen Horowitz) - Chris Dixon’s blogJeff Bussgang (Flybridge Capital Partners) - Seeing Both SidesBen Horowitz (Andreessen Horowitz) - Ben’s blogJosh Kopelman (First Round Capital) - Redeye VCMike Hirshland (Resolute.VC, formerly Polaris Ventures) - VCMike’s BlogDavid Cowan (Bessemer Venture Partners) - Who has time for thisJalak Jobanputra (FuturePerfect Ventures) - The barefoot VCHoward Morgan (First Round Capital) - Way too ealryGreg Gottesman (Madrona Venture Partners) - Stark Raving VCDavid Skok (Matrix Partners) - For entrepreneursMark Suster (GRP Partners) - Both Sides of the TableOther blogsJared O'Toole and Matt Wilson - Under 30 CEOAnita Campbell - Small Business TrendsAndrew Chen - Andrew Chen’s blogCarson McComas, Work Happy blog for entrepreneursYoung Entrepreneur BlogHarvard Business Review Blog NetworkBusiness PunditQuora entrepreneurs to follow (there are a lot of ‘must follow’ lists of entrepreneurs on Quora, of which many aren’t very active. These people are)Wikipedia, Jimmy WalesCraigslist, Craig NewmarkBlippy and Adbrite, Philip KaplanVontu & Pipewise, Michael WolfeQuora & Facebook, Adam D'AngeloFriendster, Jonathan AbramsInstagram, Kevin SystromFoursquare, Dennis CrowleyPath, Dave Morin500 Startups, Dave McClureFacebook, Dustin MoskovitzMahalo, LAUNCH, & Weblogs, Jason CalacanisPayPal, David SacksEchoSign, Jason M. LemkinWavii, Adrian AounOther people’s listsRyan Spoon, Polaris Ventures - list of Quora threads for startupsOther resources:SBA (U.S. Small Business Administration)StartupNation (Source for Small Business Advice)Notes: I tried to use mostly plain-speak when writing this. There are a lot of opinions on vocabulary and the definition of business models, business plans, etc., so if you’re hung up on those details write your thoughts in the comments, but keep in mind that the nuances are less important than the spirit of applying some rigor to picking an idea.

Here are some amazing and completely free resources online that you can use to teach yourself data science.Besides this page, I would highly recommend following the Quora Data Science topic if you haven't already to get updates on new questions and answers!Step 1. Fulfill your prerequisitesBefore you begin, you need Multivariable Calculus, Linear Algebra, and Python. If your math background is up to multivariable calculus and linear algebra, you'll have enough background to understand almost all of the probability / statistics / machine learning for the job.Multivariate Calculus: What are the best resources for mastering multivariable calculus?Numerical Linear Algebra / Computational Linear Algebra / Matrix Algebra: Linear Algebra, Introduction to Linear Models and Matrix Algebra. Avoid linear algebra classes that are too theoretical, you need a linear algebra class that works with real matrices.Multivariate calculus is useful for some parts of machine learning and a lot of probability. Linear / Matrix algebra is absolutely necessary for a lot of concepts in machine learning.You also need some programming background to begin, preferably in Python. Most other things on this guide can be learned on the job (like random forests, pandas, A/B testing), but you can't get away without knowing how to program!Python is the most important language for a data scientist to learn. To learn to code, more about Python, and why Python is so important, check outHow do I learn to code?How do I learn Python?Why is Python a language of choice for data scientists?Is Python the most important programming language to learn for aspiring data scientists and data miners?R is the second most important language for a data scientist to learn. I’m saying this as someone with a statistics background and who went through undergrad mainly only using R. While R is powerful for dedicated statistical tasks, Python is more versatile as it will connect you more to production-level work.If you're currently in school, take statistics and computer science classes. Check out What classes should I take if I want to become a data scientist?Step 2. Plug Yourself Into the CommunityCheck out Meetup to find some that interest you! Attend an interesting talk, learn about data science live, and meet data scientists and other aspirational data scientists. Start reading data science blogs and following influential data scientists:What are the best, insightful blogs about data, including how businesses are using data?What is your source of machine learning and data science news? Why?What are some best data science accounts to follow on Twitter, Facebook, G+, and LinkedIn?What are the best Twitter accounts about data?Step 3. Setup and Learn to use your toolsPythonInstall Python, iPython, and related libraries (guide)How do I learn Python?RInstall R and RStudio (It's good to know both Python and R)Learn R with swirlSublime TextInstall Sublime TextWhat's the best way to learn to use Sublime Text?SQLHow do I learn SQL? What are some good online resources, like websites, blogs, or videos? (You can practice it using the sqlite package in Python)Step 4. Learn Probability and StatisticsBe sure to go through a course that involves heavy application in R or Python. Knowing probability and statistics will only really be helpful if you can implement what you learn.Python Application: Think Stats (free pdf) (Python focus)R Applications: An Introduction to Statistical Learning (free pdf)(MOOC) (R focus)Print out a copy of Probability CheatsheetStep 5. Complete Harvard's Data Science CourseAs of Fall 2015, the course is currently in its third year and strives to be as applicable and helpful as possible for students who are interested in becoming data scientists. An example of how is this happening is the introduction of Spark and SQL starting this year.I'd recommend doing the labs and lectures from 2015 and the homeworks from 2013 (2015 homeworks are not available to the public, and the 2014 homeworks are written under a different instructor than the original instructors).This course is developed in part by a fellow Quora user, Professor Joe Blitzstein. Here are all of the materials!Intro to the classWhat is it like to design a data science class? In particular, what was it like to design Harvard's new data science class, taught by professors Joe Blitzstein and Hanspeter Pfister?What is it like to take CS 109/Statistics 121 (Data Science) at Harvard?Course MaterialsClass main page: CS109 Data ScienceLectures, Slides, and Labs: Class MaterialAssignmentsIntro to Python, Numpy, Matplotlib (Homework 0) (Solutions)Poll Aggregation, Web Scraping, Plotting, Model Evaluation, and Forecasting (Homework 1) (Solutions)Data Prediction, Manipulation, and Evaluation (Homework 2) (Solutions)Predictive Modeling, Model Calibration, Sentiment Analysis (Homework 3) (Solutions)Recommendation Engines, Using Mapreduce (Homework 4) (Solutions)Network Visualization and Analysis (Homework 5) (Solutions)Labs(these are the 2013 labs. For the 2015 labs, check out Class Material)Lab 2: Web ScrapingLab 3: EDA, Pandas, MatplotlibLab 4: Scikit-Learn, Regression, PCALab 5: Bias, Variance, Cross-ValidationLab 6: Bayes, Linear Regression, and Metropolis SamplingLab 7: Gibbs SamplingLab 8: MapReduceLab 9: NetworksLab 10: Support Vector MachinesStep 6. Do all of Kaggle's Getting Started and Playground CompetitionsI would NOT recommend doing any of the prize-money competitions. They usually have datasets that are too large, complicated, or annoying, and are not good for learning. The competitions are available at Competitions | KaggleStart by learning scikit-learn, playing around, reading through tutorials and forums on the competitions that you’re doing. Next, play around some more and check out the tutorials for Titanic: Machine Learning from Disaster for a binary classification task (with categorical variables, missing values, etc.)Afterwards, try some multi-class classification with Forest Cover Type Prediction. Now, try a regression task House Prices: Advanced Regression Techniques. Try out some natural language processing with Quora Question Pairs | Kaggle. Finally, try out any of the other knowledge-based competitions that interest you!Step 7. Learn Some Data Science ElectivesData science is an incredibly large and interdisciplinary field, and different jobs will require different skillsets. Here are some of the more common ones:Product Metrics will teach you about what companies track, what metrics they find important, and how companies measure their success: The 27 Metrics in Pinterest’s Internal Growth DashboardMachine Learning How do I learn machine learning? This is an extremely rich area with massive amounts of potential, and likely the “sexiest” area of data science today. Andrew Ng's Machine Learning course on Coursera is one of the most popular MOOCs, and a great way to start! Andrew Ng's Machine Learning MOOCA/B Testing is incredibly important to help inform product decisions for consumer applications. Learn more about A/B testing here: How do I learn about A/B testing?Visualization - I would recommend picking up ggplot2 in R to make simple yet beautiful graphics and just browsing DataIsBeautiful • /r/dataisbeautiful and FlowingData for ideas and inspiration.User Behavior - This set of blogs posts looks useful and interesting - This Explains Everything " User BehaviorFeature Engineering - Check out What are some best practices in Feature Engineering? and this great example: http://nbviewer.ipython.org/github/aguschin/kaggle/blob/master/forestCoverType_featuresEngineering.ipynbBig Data Technologies - These are tools and frameworks developed specifically to deal with massive amounts of data. How do I learn big data technologies?Optimization will help you with understanding statistics and machine learning: Convex Optimization - Boyd and VandenbergheNatural Language Processing - This is the practice of turning text data into numerical data whilst still preserving the "meaning". Learning this will let you analyze new, exciting forms of data. How do I learn Natural Language Processing (NLP)?Time Series Analysis - How do I learn about time series analysis?Step 8. Do a Capstone Product / Side ProjectUse your new data science and software engineering skills to build something that will make other people say wow! This can be a website, new way of looking at a dataset, cool visualization, or anything!What are some good toy problems (can be done over a weekend by a single coder) in data science? I'm studying machine learning and statistics, and looking for something socially relevant using publicly available datasets/APIs.How can I start building a recommendation engine? Where can I find an interesting data set? What tools/technologies/algorithms are best to build the engine with? How do I check the effectiveness of recommendations?What are some ideas for a quick weekend Python project? I am looking to gain some experience.What is a good measure of the influence of a Twitter user?Where can I find large datasets open to the public?What are some good algorithms for a prioritized inbox?What are some good data science projects?Create public github repositories, make a blog, and post your work, side projects, Kaggle solutions, insights, and thoughts! This helps you gain visibility, build a portfolio for your resume, and connect with other people working on the same tasks.Step 9. Get a Data Science Internship or JobHow do I prepare for a data scientist interview?How should I prepare for statistics questions for a data science interviewWhat kind of A/B testing questions should I expect in a data scientist interview and how should I prepare for such questions?What companies have data science internships for undergraduates?What are some tips to choose whether I want to apply for a Data Science or Software Engineering internship?When is the best time to apply for data science summer internships?Check out The Official Quora Data Science FAQ for more discussion on internships, jobs, and data science interview processes! The data science FAQ also links to more specific versions of this question, like How do I become a data scientist without a PhD? or the counterpart, How do I become a data scientist as a PhD student?Step 10. Share your Wisdom Back with the Data Science CommunityIf you’ve made it this far, congratulations on becoming a data scientist! I’d encourage you to share your knowledge and what you’ve learned back with the data science community. Data Science as a nascent field depends on knowledge-sharing!Think like a Data ScientistIn addition to the concrete steps I listed above to develop the skill set of a data scientist, I include seven challenges below so you can learn to think like a data scientist and develop the right attitude to become one.(1) Satiate your curiosity through dataAs a data scientist you write your own questions and answers. Data scientists are naturally curious about the data that they're looking at, and are creative with ways to approach and solve whatever problem needs to be solved.Much of data science is not the analysis itself, but discovering an interesting question and figuring out how to answer it.Here are two great examples:Hilary: the most poisoned baby name in US historyA Look at Fire Response DataChallenge: Think of a problem or topic you're interested in and answer it with data!(2) Read news with a skeptical eyeMuch of the contribution of a data scientist (and why it's really hard to replace a data scientist with a machine), is that a data scientist will tell you what's important and what's spurious. This persistent skepticism is healthy in all sciences, and is especially necessarily in a fast-paced environment where it's too easy to let a spurious result be misinterpreted.You can adopt this mindset yourself by reading news with a critical eye. Many news articles have inherently flawed main premises. Try these two articles. Sample answers are available in the comments.Easier: You Love Your iPhone. Literally.Harder: Who predicted Russia’s military intervention?Challenge: Do this every day when you encounter a news article. Comment on the article and point out the flaws.(3) See data as a tool to improve consumer productsVisit a consumer internet product (probably that you know doesn't do extensive A/B testing already), and then think about their main funnel. Do they have a checkout funnel? Do they have a signup funnel? Do they have a virility mechanism? Do they have an engagement funnel?Go through the funnel multiple times and hypothesize about different ways it could do better to increase a core metric (conversion rate, shares, signups, etc.). Design an experiment to verify if your suggested change can actually change the core metric.Challenge: Share it with the feedback email for the consumer internet site!(4) Think like a BayesianTo think like a Bayesian, avoid the Base rate fallacy. This means to form new beliefs you must incorporate both newly observed information AND prior information formed through intuition and experience.Checking your dashboard, user engagement numbers are significantly down today. Which of the following is most likely?1. Users are suddenly less engaged2. Feature of site broke3. Logging feature brokeEven though explanation #1 completely explains the drop, #2 and #3 should be more likely because they have a much higher prior probability.You're in senior management at Tesla, and five of Tesla's Model S's have caught fire in the last five months. Which is more likely?1. Manufacturing quality has decreased and Teslas should now be deemed unsafe.2. Safety has not changed and fires in Tesla Model S's are still much rarer than their counterparts in gasoline cars.While #1 is an easy explanation (and great for media coverage), your prior should be strong on #2 because of your regular quality testing. However, you should still be seeking information that can update your beliefs on #1 versus #2 (and still find ways to improve safety). Question for thought: what information should you seek?Challenge: Identify the last time you committed the Base Rate Fallacy. Avoid committing the fallacy from now on.(5) Know the limitations of your tools“Knowledge is knowing that a tomato is a fruit, wisdom is not putting it in a fruit salad.” - Miles KingtonKnowledge is knowing how to perform a ordinary linear regression, wisdom is realizing how rare it applies cleanly in practice.Knowledge is knowing five different variations of K-means clustering, wisdom is realizing how rarely actual data can be cleanly clustered, and how poorly K-means clustering can work with too many features.Knowledge is knowing a vast range of sophisticated techniques, but wisdom is being able to choose the one that will provide the most amount of impact for the company in a reasonable amount of time.You may develop a vast range of tools while you go through your Coursera or EdX courses, but your toolbox is not useful until you know which tools to use.Challenge: Apply several tools to a real dataset and discover the tradeoffs and limitations of each tools. Which tools worked best, and can you figure out why?(6) Teach a complicated conceptHow does Richard Feynman distinguish which concepts he understands and which concepts he doesn't?Feynman was a truly great teacher. He prided himself on being able to devise ways to explain even the most profound ideas to beginning students. Once, I said to him, "Dick, explain to me, so that I can understand it, why spin one-half particles obey Fermi-Dirac statistics." Sizing up his audience perfectly, Feynman said, "I'll prepare a freshman lecture on it." But he came back a few days later to say, "I couldn't do it. I couldn't reduce it to the freshman level. That means we don't really understand it." - David L. Goodstein, Feynman's Lost Lecture: The Motion of Planets Around the SunWhat distinguished Richard Feynman was his ability to distill complex concepts into comprehendible ideas. Similarly, what distinguishes top data scientists is their ability to cogently share their ideas and explain their analyses.Check out https://www.quora.com/Edwin-Chen-1/answers for examples of cogently-explained technical concepts.Challenge: Teach a technical concept to a friend or on a public forum, like Quora or YouTube.(7) Convince others about what's importantPerhaps even more important than a data scientist's ability to explain their analysis is their ability to communicate the value and potential impact of the actionable insights.Certain tasks of data science will be commoditized as data science tools become better and better. New tools will make obsolete certain tasks such as writing dashboards, unnecessary data wrangling, and even specific kinds of predictive modeling.However, the need for a data scientist to extract out and communicate what's important will never be made obsolete. With increasing amounts of data and potential insights, companies will always need data scientists (or people in data science-like roles), to triage all that can be done and prioritize tasks based on impact.The data scientist's role in the company is the serve as the ambassador between the data and the company. The success of a data scientist is measured by how well he/she can tell a story and make an impact. Every other skill is amplified by this ability.Challenge: Tell a story with statistics. Communicate the important findings in a dataset. Make a convincing presentation that your audience cares about.Good luck and best wishes on your journey to becoming a data scientist! For more resources check out Quora’s official Quora Data Science FAQ

Read every startup, tech, legal, pr, advertising blog and put them on your RSS reader. What are the best blogs on startups?Help define the mission and culture of the companyWrite out a functional test plan, start using it on the early stages of the development so that it's not overwhelming when it's "done."Find people that you trust and have them get excited about the project so you can convert them to early beta/alpha testersWork on SEO backlinking, directory submissions, keyword research etcWrite copy for error messages, description, guides, tutorialsStart a FAQBuild a community off-site (LinkedIN, Facebook Groups, Fan Pages, etc)Plan out marketing ideas and concepts that complement your product/solutionEvaluate media buy costs, learn those tools and platformsInterview PR agencies (don't hire them, just learn what PR tactics can be done and do them yourself)Talk to a 100 people about the conceptBuild and maintain the structure of the WikiCreate copy for the transactional email messages (Thank you for registering, launch email, forgot password email, invite emails, etc)Start talking to people that can help your tech team in any way possible. If you can't sell the idea to get some people to help, then it will be a long way to go when you start thinking about recruiting. (Note, make sure to get a legal work-for-hire waiver if people do help)Talk to your friends who became lawyers for free advice.Talk to your friends who became venture capitalists for free advice.Start a BlogBring food, coffee, 7-11 runs for the team (seriously, don't make this an ego thing, this really helps the team's morale, everybody appreciates the little conveniences so they can keep their minds focused on code)Build your 10 page deck, answer these questions for yourself and team: http://blog.guykawasaki.com/2005/12/the_102030_rule.htmlDevelop the information architecture of the marketing website - this is the website people see before they register. Depends on your product/service, but it usually has a homepage, features, pricing, solution, faq, support, contact us, etc.Be the social media spokesperson, start engaging and establishing a social media context and relevance.Learn any of the 100's of tools to monitor performance - SEO, A/B, PPC/SEM, Social Media, Web Analytics (CTR, Conversion, Bounce Rate) Conversion Funneling. Create the a list of metrics that are actionable and the ones that matter to your business: http://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-versionWhy don't you pick up a book and learn how to code? Plenty of people learn the basics, you should too - (you know, Dennis Crowley? from Foursquare? He's not "technical" but he helped write the first version... ) You can do it too! Did Dennis Crowley write the original code for foursquare (Dodgeball) himself?Or follow this question: How do I start to learn coding or programming?