An Introduction To Project Management - Etc Corp: Fill & Download for Free

I’ve run a boutique data science consultancy called Boxelder Analytics for the last six years so I will give some recommendations that will hopefully set you up for success.The list of improvements and preparations you could make is probably close to never-ending, so I have distilled what would be a long-winded answer into a less long-winded answer expressed in several general points.Here are some things you can start now:Professional Development: continue to develop your skills as a data scientist and technician. Build a roadmap and stick to it consistently over the coming years. Regardless of starting a consultancy, you should be doing this anyway as a data scientist. It’s hard work. Put aside an hour or more a night instead of watching television, games or other distractions and tackle a prioritized list of concepts. Generate goals and break them down into monthly or quarterly milestones. Use something like the Data Science metro map below to guide your development. This might be somewhat dated, but probably the most comprehensive representation I’ve seen. Stick to the basics and don’t be distracted by shiny objects. Stick to Python and aim to deploy your own analytical web applications utilizing the core concepts. Get these products in front of people and get feedback. Ask a local business if you can solve problems for them and use it to teach yourself. If you are going to be hiring, managing and leading other data scientists and technicians, then you need to be proficient from a technical standpoint. When I was an officer in the United States Marine Corps, we would develop technical proficiency using weapons systems and communications equipment that a more junior Marine would be using day in and day out, but having that proficiency enabled me as a decision maker to understand the capabilities and limitations of these assets and employ them more effectively. For instance, we might train and equip a unit with satellite-based communications equipment if their traditional VHF-based equipment is going to exceed its range or otherwise be impeded by the terrain in a given area for an operation. You can’t be an expert in everything in data science, but you can develop a proficiency and set yourself up for better decision making in the future by generating this technical experience.Develop Management Skills: take jobs in your current or other future roles that involve the management of data science projects. Ask your current managers for additional opportunities and become involved in developing workflows for your current company that enable you and others to do your job more effectively. Ask to assist in the planning process. You will do a lot of this when you are running your consultancy. Read as much as you can about project management and agile specifically. Traditional software development and project management techniques do not apply out-of-the-box to the data science workflow and there is not a good standard from which to work (at least I have not found it yet and have had to develop management systems based on my own experience). Read about what others are doing and tweak it to fit the services you’ll be offering (see below). Also read about leadership in other fields and apply it in your current role.Build & Maintain Your Own Assets: develop your own platforms to make the consulting process easier to manage and deploy solutions to your future consulting clients. Develop workflows and standards for notebooks that you can use in the future. Develop utility modules in Python to support these workflows (e.g. connect to a remote MySQL instance on a virtual server using “SSH Tunnel Forwarded” and “SQL Alchemy”). Define what your data science process looks like and build all of the utilities around these processes so that you are not reinventing the wheel every time you implement a solution. Start off by solving toy problems or problems for a local business and build these utilities into platforms that you can use to deploy solutions more rapidly. Also, consider how your clients are most likely going to consume the outputs of your modeling and data science efforts. Consider developing enough of a competency in web development to deploy solutions as basic web applications. Also consider using APIs to communicate the results of models to your clients. They can easily integrate this into their existing systems. A lot of folks use Flask to do this, but I use Python’s Django and Django REST Framework to deploy these solutions. I have even abstracted the API approach and built a SaaS product called Hemlock whereby users can deploy their models directly from a Jupyter Notebook and instantly share them with their clients. This started off as an internal project that was then made customer-facing. Do all of this on your own systems at home and do not use any resources from your job to develop these platforms or systems. Reread all of the stuff you owned up to during the hiring process to see if anything there could impact intellectual property ownership/licensing/et cetera in the future.Start Marketing, Branding & Relationship Building Now: start building your reputation now and know all of the folks around town who are involved in data or data science. Ask them for introductions and attend events in the area. Introduce yourself to people everywhere. You never know who you’ll meet on the ski lift, for instance. Could be your future client. Get introductions to local business owners and build your network slowly over time. Take advantage of feedback or insight from these business owners over a coffee or beer by asking where their pain points are, how they currently use data to make decisions, if they have any ongoing initiatives or if they would be interested in partnering in the future. Start writing about your experiences and publishing in some way. Communicate with these folks via a monthly email or something similar. Blog about your experiences and write about things that can add value for folks. Retain these contacts and periodically check in. Relationships and adding value are at the heart of building a consulting business. There is nothing more important.Don’t Ignore the Business Side of The House: the premise of a consultancy is that you can offer your expertise, insight, abilities and those of your employees to add value to a client’s business. There are two fundamental ways that you can do this: (1) enable them to generate additional revenue or (2) set them up to reduce costs (or both). Some derivatives of this are that you can enable them to do things more quickly (i.e. automation) and this will impact the cost side of things or you can impact some stakeholder of the client that cannot be easily defined in dollars and cents (e.g. patient satisfaction). You must be able to measure success from this perspective. Even if it is difficult to measure success (or failure), it is in your best interest to do so. Understanding how you impact your client’s organization is critical to your existence. If you are falling short, then you need to know and course correct to improve the situation. Also, you should understand the role of risk in these types of projects and account for it in the contracts. Not all data science efforts succeed. This can occur due to poor data, lack of support from the client in terms of implementation, etc. I typically structure contracts to account for these and other risks by phasing things out. For instance, it makes sense to get an idea of what the data looks like prior to building a model. I typically bundle an assessment of the data and business along with definition of the business problem early on to mitigate these risks. I’d rather identify these issues up front and course correct (e.g. alter the business problem and associated deliverable) than find out after perhaps the wrong problem has been solved.Identify Needs Now & Develop Services: keep a list of all the problems you come across over the upcoming years. Write all of the pain points and associated opportunities down in a notebook after speaking with folks that run or manage companies. I use Evernote to do this and I try to identify the trends that I see over the months and years. These translate into business processes and services that I can offer. Understand where the gaps are in the local economy from a competitive standpoint and fit your services into that marketplace. Understand where the industries are moving and where they are growing and take advantage of these trends. Stay within specific industries in order to build a competency there and not spread yourself too thin. For instance, are you going to focus on Insurance? Finance? Retail? Keep some trusted advisors and contacts in this industry that will give you honest feedback about your services, opportunities, etc. Here is a link to my Services page at Boxelder Analytics. This might help and is being continually improved, but they have been born from my experience and trends I have seen in the market after working with many companies and interacting with many folks in various industries.Be Patient: do not expect to grow into a successful business overnight. It takes months and years to successfully put all of these things into place. You’ll fail in some respects and will learn from these failures. Don’t be afraid of this and embrace failure as a way to learn (just don’t fail too hard). It is great that you want to start leaning into this so early and this will help you to succeed in the long-run. Keep in mind that it is a long-term investment. Treat relationships with respect and integrity. Do what is right at the end of the day and understand why your clients have brought you on board. Be frank and direct with them about issues and don’t play games. Ask questions and be willing to learn. A good consultant asks really good questions. A brand takes a long time to build. It is born from consistently interacting with clients and customers and delivering quality solutions over years.Keep in mind that you are asking about running a business. There will most likely become a point when you are doing less data science and more management. People have to get paid and contracts have to be written. Expose yourself to those things as much as you can in your current role. You’ll do more contract negotiating, legal review, billing, admin, paychecks, etc than you’d expect in this role, so don’t forget to understand all of the things it takes to run a business.Final note: wake up tomorrow and start running your own analytics consulting firm. You don’t have to secure client #1 tomorrow, but maybe start with some of the things mentioned above. Build the foundation that is going to make you successful in the coming years. This will largely rest on your personal abilities early on and then you’ll rely on others. Early on it will be your fortitude and ability to persevere and navigate obstacles that matters more than anything. It’s not an easy road, but can be wildly satisfying on both personal and professional levels. I would not trade the hardship for anything else. This was somewhat stream-of-consciousness, but hopefully it helps.If anyone has any points to add or other feedback, then please make a comment. I’d love to hear from others.

If you want to be an accountant/CPA, then I would advise an accounting degree (like the other answers here). Otherwise it is not necessary.Accounting is important, but I cannot tell you how many times I have heard a successful investor claim "I'm not an accountant" to explain why they were glossing over some detail. To be clear, these individuals do have an understanding of accounting, it’s just not as thorough as what might be expected of a talented CPA.What's most important is understanding what creates and destroys value. The best exposure you could get would be on the job training (M&A, PE, HF, etc.) but I assume you would not be asking if you had that exposure. So start with some simple accounting texts:VocabularyAmazon.com: Accounting Made Simple: Accounting Explained in 100 Pages or Less (9780981454221): Mike Piper: BooksIn my experience, people who claim that they simply cannot understand finance don’t spend enough time on vocabulary. The math is pretty simple. It’s just explained in a different language. Learn the language and everything else will follow.Integrated Financial Statement ModelIt may seem like a stretch, but once you have a grasp of the vocabulary I would work through building an integrated financial statement model (income statement, balance sheet and cash flow statement) with a five year projection. This exercise is what caused everything to “click” for me as an analyst. I built ASimpleModel.com to share this learning experience (free video-driven instruction):Start with Introduction to Financial Statements: This video series introduces the financial statements in the context of building a financial model. In other words, it emphasizes the relationships between the financial statements. When you finish this video series, take a break, and write down in your own words how the financial statements link to each other (sidenote: this is one of my favorite interview questions for entry-level analysts).Then move on to Integrating Financial Statements: This is a critical process to understand. As you work through this exercise pay attention to cash. You want to be hyper aware of the line items that generate or consume cash (this will make more sense in the videos).As you forget words take the time to look them up. To avoid having to flip back and forth between texts, use Investopedia - Educating the world about finance every time you come across new vocabulary.ValuationThen move on to texts that explain value:The Little Book of Valuation - written by Aswath Damodaran, a legend in the world of valuation. You should also consider his blog: Musings on Markets.Valuation: Measuring and Managing the Value of Companies, 5th Edition: 9780470424650: Economics Books @ Amazon.com (this one is dense, but I used it as a reference for years - an incredible resource)Financial Shenanigans: How to Detect Accounting Gimmicks & Fraud in Financial Reports, 3rd Edition: Howard Schilit, Jeremy Perler: 9780071703079: Amazon.com: Books (focuses on how financials are manipulated and will train your eye to look for irregularities)Annual ReportsThen (to echo David Ecale) start working through 10-Ks (annual reports) and pay attention to the notes. Read the shareholder letters and think about what the CEO is attempting to communicate to individuals interested in the companies ability to create value. You will come across sections like “Summary of Significant Accounting Policies” and “Recent Accounting Pronouncements” that appear dense and possibly not worth your time. Read them with Investopedia handy - it’s an education in accounting.If you want a good place to start - John Deere (link to annual report) - as practice, make sense of the following: “The one-time blacksmith shop has become a kind of bank - at least, operating income from the Deere Captive finance unite, John Deere Capital Corp., has grown to eclipse the earnings from shrinking equipment sales. Of overall operating income in the three months to Jan. 31 ag and turf sales chipped in $144 million, or 35%; financing activity, $194 million, or 48%. As recently as fiscal 2013, the respective contributions to operating income were 79% and 15%.” Grant’s Interest Rate Observer March 11, 2016Under Armour is another interesting case-study. They recently experienced strong growth in sales, but working capital outpaced this growth. Go through their 10k and examine the impact this has on cash.Finally, pick up Berkshire Hathaway Letters to Shareholders, 2012: Warren Buffett, Max Olson: 9781595910776: Amazon.com: Books - amazing amounts of insight. If you do not want to pay for the book just go to Page on berkshirehathaway.com - you can download the letters one at a time going back to 1995.More Reading…For the self-motivated an abundance of material exists. For a list of additional books - ASM Books.

Please read the details as given below:-http://M.Sc. Geoinformatics: Top InstitutesListed below are some of the top institutes in India that offer the course.Name of InstituteCityAverage FeesTeri UniversityDelhiINR 3.9 lacs (Course)Symbiosis Institute of GeoinformaticsPuneINR 4 lacs (Course)Amity Institute of Geo-Informatics & Remote Sensing (AIGIRS)NoidaINR 3 lacs (Course)IIRSDehradunINR 50,790 (Course)School of Applied Science and Agriculture, Suresh Gyan Vihar UniversityJaipurINR 1.5 lacs (Course)Bharati Vidyapeeth Institute of Environment Education and ResearchPuneINR 2.25 lacs (Course)Savitribai Phule Pune UniversityPuneINR 25,500 (Course)Birla Institute of TechnologyRanchiINR 2.5 lacs (Course)Hemwati Nandan Bahuguna Garhwal UniversityUttrakhandINR 80,000 (Course)Central University of JharkhandJharkhandINR 30,000 (Course)Central University of KarnatakaKarnatakaINR 25,000 (Course)Madurai Kamaraj UniversityMaduraiINR 15,000 (Course)Sangam University (SU, Bhilwara)BhilwaraINR 55,000 (Course)http://M.Sc. Geoinformatics: EligibilityListed below are the minimum criteria which candidates interested in pursuing the course are required to fulfil, in order to be eligible to apply for the course.Successful completion of graduation in the Science stream, from a recognized university.Graduation needs to have been completed in any ofScience/ EngineeringB. Arch.Economics/ Mathematics/ Statistics/ GeologyA minimum aggregate score of 55% (50% for SC/ST candidates) at the level of graduation.http://M.Sc. Geoinformatics: Admission ProcessMost institutes offering the course admit students based on performance in a relevant entrance test. Often, some institutes offering the course in the country offer admission to eligible candidates based on their performance at the level of graduation.Admission process generally varies across colleges.The entrance test typically involves the following sections of assessment:Proficiency in EnglishAnalytical reasoningQuantitative abilitySome such entrance tests conducted in the country for admission to the course are:SIG PuneIIRSLatest Master of Science [http://M.Sc] (Geoinformatics) Admission AlertJamia Millia Islamia (JMI) Admission 2020: Courses, Cut Off, CriteriaNetaji Subhas National Institute of Sports Admission 2020: Courses, Fees, EligibilityIIT Hyderabad Admissions 2020: B.Tech. & M.Tech. Selection, Ph.D., Application, Entrance ExamIIT Delhi Admission 2020: Cut Off, Fees, Eligibility, CoursesTIFR Admission 2020: Entrance exam, Application formHislop College Nagpur Admission 2020, Fees, Courses, Selection criteria, Eligibilityhttp://M.Sc. Geoinformatics: Syllabus and Course DescriptionSemester 1Semester 2Environmental statisticsDigital image processing and information extractionApplied mathematicsSpatial data modelling and GIS applicationsProject managementLaw and policy for maps and remote sensingPrinciples of GIS and GPSPhotogrammetryResearch methodology and thesis writingTechnical Writing (Communication skills and technical writing)Introduction to sustainable development-Fundamentals of computers and programming-Principles of cartography-Principles of remote sensing-Semester 3Independent StudyEnvironmental modellingMultivariate data analysisMinor projectAdvances in GIS and current trendsIntegrated impact assessmentAdvances in remote sensingIntegrated watershed managementWildlife conservation and managementGlacier hydrologySatellite meteorologyGroundwater hydrology and management-Environmental management systemSemester 4Major projecthttp://M.Sc. Geoinformatics: Career ProspectsSuch professionals acquire relevance in light of the following facts:The dream of the digital India, Smart cities cannot be completed without the use of Geoinformatics technology.Almost no developmental project is complete without geospatial information.The country is facing a shortage of skilled Geoinformatics professionals.The discipline is applied across diverse disciplines.The industry is rapidly adopting Geoinformatics technologies for efficient delivery of products or processesPopular hiring organizations include:Reliance IndustriesReliance JioLavasa CorpL&TSuzlon.Many IT companies are handling overseas projects based on Geospatial technologies, such as:InfosysTCSHCLAccentureTech MahindraGoogleiGATE, etc.Insurance sector companies like WILLIS RE, SWISS RE are using Geospatial technology significantly.Central and State government departments are using Geoinformatics application, such as the following:National Remote Sensing Centre (NRSC HyderabadNorth East Space Application Centre, (NESAC Shillong)Regional Remote Sensing Centers (RRSC Kharagpur, Dehradun, Jodhpur, Nagpur and Bangalore)Indian Space Research Organization, (ISRO).Related http://M.Sc. Geoinformatics courses are:M.Sc. AstronomyM.Sc. Earth ScienceM.Sc. Applied MathematicsMaster of Science (M.Sc.)