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I would like him to find out who Lori Erica Kennedy really was.On Christmas Eve, 2010, Lori drove to her ex-husband’s parents house, stopping her car in their driveway.Then she shot herself in the head.In her house her ex-husband found a strongbox, hidden in a closet: during their marriage, Lori had designated several places around the house she had forbidden him to go. The back of that closet was one of those places.Inside the box, there was a birth and death certificate of a small girl named Becky Sue Turner, a fraudulent application for a Social Security number in the name of Lori Kennedy; documentation related to a name change, from ‘Becky Sue Turner’ to ‘Lori Kennedy’; strange messages, a fake recommendation letter in behalf of Lori from a man who doesn’t exist, and more.Lori ... Becky Sue ... [Social Security Administration investigator Joe] Velling just calls her Jane Doe. He’s paged through the clues to her life over and over.“The reason I can’t find anything prior to 1988 is because she’s very good,” he said.He pulls out a timeline. On one side is Jane Doe’s life as Lori and, briefly, Becky Sue. On the other side is nothing.It took Jane Doe two months to take over the identity of someone she wasn’t. First, she got a copy of Becky Sue’s birth certificate from Bakersfield, Calif. In those days, many counties would just mail a copy to whoever asked.Notably, Becky Sue was born in one state but died in another — it says so in a news clipping. That suggests Jane Doe knew what she was doing, because this kind of separation reduces the chances of being tripped up by some state database.She got an Idaho ID card in Becky Sue’s name in Boise, claiming she was 18 years old.“What this tells me is that Jane Doe was in Idaho in 1988,” Velling said. This tidbit, discovered just last week, strengthens the hypothesis that she was from the Northwest. She also kept a mail drop in Boulder City, Nev., which forwarded her mail to Dallas.After getting the ID, she went to court in Dallas to change her name, legally, from Becky Sue Turner to Lori Erika Kennedy.Next came the most important step: getting a Social Security card, the holy grail of identity theft.Today, most children get Social Security numbers at birth. Back then, you could easily get your card as a teen. That’s what Jane Doe did. She became Lori Kennedy, a blank slate, with government ID.“Once I have that name change and the Social Security number, I’m really a whole new person,” Velling said.The whole process took less than two months.As Lori, she got into college without providing any high-school transcripts. “She took the GED,” Velling said. “No clue there.” She graduated from the University of Texas in Arlington with a degree in business.He tracked down a few friends and colleagues from years ago. One said she had been working as a dancer at a “gentleman’s club” in the early 1990s, according to Velling. A clue, perhaps. But no one he found knew anything about Lori before 1988.In the strongbox there also were letters of reference from an employer and a landlord. And the scribbles: North Hollywood police. 402 months. Ben Perkins, an attorney.Was she in legal trouble? Facing 402 months in prison? Velling chased the leads.The job reference appears to be bogus, signed by someone who never existed.Lawyer Ben Perkins? He had no recollection of her.Velling ran photos of Jane Doe through every facial-recognition database he knew. Nothing. He sent her fingerprints to the FBI. They didn’t match anyone in their criminal files.“If she was facing prison time,” he thought, “you would have thought there would be fingerprints.”He had the fingerprints compared with those on file with the Department of Homeland Security. Nothing.He learned from medical records that she had breast implants. And for a moment, Velling thought he had a solid lead — implants, he learned, have serial numbers, and serial numbers lead to doctors’ records. But it appeared she got them after she had become Lori. And besides, she was cremated.“This case is so difficult,” he said, “because the trail’s dead.”[1][1][1][1]Pictures of the contents of the strongbox can be seen in this gallery of the Seattle Times.Who was she?Footnotes[1] She stole another’s identity, and took her secret to the grave. Who was she?[1] She stole another’s identity, and took her secret to the grave. Who was she?[1] She stole another’s identity, and took her secret to the grave. Who was she?[1] She stole another’s identity, and took her secret to the grave. Who was she?

I think anyone can transfer over regardless of age or background. They just need the motivation and commitment. To add to this question I think anyone can do this in 6 months.This is some content from an earlier piece I wrote (https://www.linkedin.com/pulse/from-0-100k-data-science-job-6-months-ben-taylor-ai-hacker/) that I think satisfies the answer to this question:Across the way, I see people that I care about trying to break into this field. Wondering what to study, what skills they need, feeling clueless about how to get that first real data science job in this market. This answer is for them.Many experts will disagree with me and say it is not possible to do this. They will say that there is no realistic pathway for someone to go from 0 to a serious data science job in such a short amount of time. Especially, without going through a paid program to do so. They will reference 4-8 years of graduate education as a necessary step to routing someone to this point. I disagree.Hypothetical ResetTo understand the mechanics of this I will throw it on myself. I will create a hypothetical situation. I am going to delete all of my work war wounds and scars, lessons learned, network connections, academic credentials, work experience, and knowledge.Experience And Credentials = 0My resume has suddenly gone from this (left) to this (right)Network Benefit = 0In addition to losing any experience credibility, my help network will vanish. My network of recruiters, data experts, conference organizers, publishers, followers, and more importantly decision makers who could hire me... I am now a network of 1.Data Science Powers = 0Programming and math have digressed to that of a new high school graduate. I have no memory of any of my past projects, lessons learned, or language familiarity.Before I pull the trigger on this reset I get to write myself a letter, which I will have as a guide.Dear Ben,You have a TON of work cut out for you during the next 6 months to land that $100K+ data science job. Stacks of books to read, video tutorials to watch, plenty of uncomfortable networking, and public speaking on subjects you know nothing about. Scared? You should be. Success? Absolutely, but you just need to listen to everything I am about to tell you. First you need to go and buy a laptop that you enjoy typing on, with a trackpad you can tolerate. A refurbished/used Macbook air might be a fine starting point. You will be spending 3-5 hours per day on this thing so make it count.Programming:Starting now you will spend a minimum of 3 hours per day doing python programming tutorials (*EDITED: spin up tutorials with R, Julia, Java, and Octave so you are familiar but I'd still say focus on being a python expert). Start by searching YouTube for "Google Python Class Day 1 Part 1", go through the whole series and others. Keep searching for python tutorials and lessons online that work for your current understanding. Once you have started to feel more comfortable with python then start looking for tutorials on numpy, sklearn, pandas, and matplotlib. I would also order "Python Machine Learning" by Sebastian Raschka on Amazon. You need to understand every page of this book during the next three months, and show that by literally marking and writing on each page in red ink.Network:Look up the local meetups for data science and python. Plan on going to ALL of these meetups and local conferences during the next 6 months. When you go there, introduce yourself to new people and connect with them on LinkedIn and Twitter afterward. Also, if there are speakers or organizers make sure you connect with them and work to form meaningful connections with them. They will have the most influence on your future. During the next 3 months you will be presenting at these meetups. Set up a LinkedIn profile, connect with local people at these meetups, once you have more than 20 local connections start connecting to every single data scientist you can find on LinkedIn and every data science recruiter to get over 500 connections. As you build momentum and network size these future connections will be easier to get accepted. Your tag line under your name on LinkedIn will be: "Data Science Enthusiast". As you cross milestones publish what you have learned on your blog and encourage comments and feedback. As you become more sophisticated the value of your posts will grow.Statistics / Math:For someone who is truly entry level I like the dummies books:Work through that. Make sure you understand the basic concepts of mean, median, mode, std, skew, and histograms. Now start searching for online tutorials on entry level statistics, or statistics for engineers. I would also start searching for basic tutorials on linear algebra, especially anything using numpy with python.Foundation gaps:Your biggest issue right now is that your foundation looks like swiss cheese, you have holes everywhere. You need to find these gaps, and fill them as quickly as possible. One option might be to go to http://scikit-learn.org/stable/, see the topics supervised learning, unsupervised learning, clustering. You should start following through on all of these topics and understand the algorithms below them. If you can't understand them (i.e. k-means, or logistic regression) look them up online and see if you can find a YouTube tutorial, there are some great ones out there. If you are still stuck save those questions for your meetup where you can ask someone directly what they would recommend. Also, the python ML book mentioned earlier should help.Finding A Friend/MentorIf your drive, passion, and motivation are maxed out that can be detected. If you are going to meetups and showing a clear improvement in your abilities based on your efforts it will be easier to engage a mentor. Nothing is worse than someone who wants to become a data scientists but lacks the drive, passion, or focus to do so. They remind me of limp handshakes and over cooked spaghetti noodles. A mentor or friend in this space can help direct you on filling in your gaps, and they can also inspire you for topics you can present on at the meetups.Final steps:I'm running out of time for this letter so I am going to cram a final push in here. Start going through the UCI data repository and making sure you can understand python machine learning examples that run on some of these datasets (MNIST, Boston Housing, Iris flower, Titantic deaths, etc..). Once you feel comfortable there go to Kaggle and make sure you understand some of the solutions and approaches, ask your mentor for help if you get stuck on a concept. Start using jupyter.org notebooks and matplotlib for your testing/development. I would also install Docker and learn how to launch Jupyter notebooks from that and install missing packages through apt-get or pip. I would scan Upwork, the world's largest online workplace or Upwork, the world's largest online workplace for ANY machine learning related jobs that I think I can do. I don't care if I get paid $1/hr, I need that experience on my blank resume. As I start doing more jobs and feeling more confident that pay will gradually go up.Deep learning:So much to learn... really so much, but if you hack at least 3 hour per day on python programming, and 2 hours on machine-learning/stats you can start filling in those holes. Deep learning is a very exciting topic that I would include in your data tool-kit. This might be weird but I know my brain wiring is the same so I would watch my own hour long deep learning introduction video on YouTube: https://www.youtube.com/watch?v=lr3ZZAyHgsM. If possible I would try to find a free internship or even ask my mentor if I could shadow them and just look over their shoulder while they hack on a project. I would keep the books flowing as well and as I have bandwidth I would purchase any and all recommendation books around python and data science. Even books on the same topic can take a different approach and open your eyes to new perspectives and understanding.To land the first job I will need to show historical consulting where I am billing at the $100+/hr rate. I also need to focus heavily on my local network to the point where I have referrals referencing me based on interactions or local presentations. I would also ask several local peers about their opinion on why I would or would not be able to secure a data science job at the pay range I want.Community Bonus!Great news, before I lost everything I got some feedback from the community in the comments below. The community doesn't like my R vs Python comment. So time permitting I think it is worth walking through some R introductions and examples once you feel like a good programmer. Might as well keep going and spin up Julia, Java, Octave, and Torch. Having only 1 language on your resume can seem limited, but having 10 doesn't help either. I like candidates who are experts at 1 and familiar with a handful of other languages. Also, originally I said 1-2 hours per day, where the community said 5-6. I would tend to agree and might even say 8-10, but I know if I say that I'll get backlash on being anti-family/anti-life. So 1-2 is most likely too little, and 5-6 is really solid. 8-10 with the right focus and energy and you'll have multiple offers to consider in 6 months.*******************************************If this article was useful and you want to see more like it feel free to send bitcoin here as a thank you: 1Ck7Y8wwtPseYk47upKrnWZuKfzCLwvUDh

1. Learn to negotiate the best price without doing too much work: Come up with a list of agents or vendors and send them a slightly personalized email or leave them a voice mail telling them,"Hi Frank, I found your name online when I was looking for [thing I'm looking for] and I think you may be able to help me out.People naturally want to be helpful.I'm requesting quotes from a few other brokers in the state, so I wanted to invite you to quote me on [exact thing with specific configuration options].You've established that this isn't going to be an automatic sale for them. They are going to have to truly beat out their competitors. Sales folks know that it's hard to beat prices point blank, so they are going to try to sell you on options or make it difficult to compare apples to apples. By specifying exactly what you want, you clarify that you've done your research, and the best thing for them to do is just offer you their best price and try not to waste too much of their time on a low-margin sale.Right now, price is the biggest priority for me so I'm really shopping around to get the best deal.Clarify that you're not looking to throw in warranties, or free marginal upgrades, but you're interested in price, so if you want to get my sale, compete on price.I'm hoping to make a decision within the next three days. I'm looking forward to hearing from you! Thanks, [Your name]."Again reaffirming that you are a serious buyer, you're not a window shopper. Their decision right now can win or lose the sale.When the first round of quotes come back, send a follow up email to a few of the runner-up vendors letting them know that you found someone who was able to get a better price, and you'd like to see if they can get special approval to improve upon their quote. Repeat as long as people are willing to lower prices.When you get to the lowest price, now find the vendor who is most convenient for you, and ask them to price match your best price. Say something like, "I really prefer to buy locally, your office is right by my work and I've heard great recommendations and your customer service [yada yada yada]." If they can match it, go with them, otherwise go with your best bid.2. Find creative ways for other people to pay your expenses. I'm not saying to be a leech. I'm saying to find ways for other people to have an advantage in paying for something you need. For example:If you're buying a house, buy one with a finished basement or buy a duplex and upgrade it to the point that you can rent it out. Now you're making back close to half of your mortgage.Combine business trips with vacations and get free airfare.3. Look at the big picture for your finances and look for big wins and easy wins. The first urge in budgeting is to restrict yourself from your favorite things in order to save money. Don't. These are the things most worthy of your money. Instead, find the biggest expenses. Spending $200/week in groceries? Plan for 20 minutes a week and get it down to $100. Go out to eat 4+ times per week because you don't have anything planned for lunch? Plan it out so that you know every meal you're going to have for the week at the beginning of the week. Now look at recurring expenses. $25 for a 90-day prescription at Walgreens? It's $11 at Kroger. Easy win.4. Find ways to get other people to work for you. Spend the time in a more effective manner. Are you switching insurance? Get your agent to get a cancellation letter for you. Are you specifying parts for a project at work? Get your vendors to search the catalogs that meet your spec. Get applications engineers to explain to you the,"best approach" rather than piecing it together from the help file. Pay online assistants to outsource the time consuming drudgery if you can better use the time to get maximum enjoyment or a better return.5. When bootstrapping a business, make presales before you make product. This validates the demand for your product, and gives you funding to pay all the capital costs and insulate you from the risk.