- On Thursday, June 7, 2018
- By Read More
'First you have to learn: Linear Algebra, Convex Optimization, Differential Equations, Calculus, Algorithms, Distributed Computing, Databases (SQL & NoSQL), Machine Learning, Probabilistic Modeling, Deep Learning, Natural Language Processing, Data Visualization, and don't forget Scala for functional programming, and Hadoop, and Big Data, and Experimental Design, and Functional Analysis, and......'
Your eyes glaze over as you see yourself going back to a dimly-lit lecture hall for the rest of your life.
You just read yet another a list of books you MUST COMPREHEND, MOOC's you MUST TAKE, and statistical programming libraries you MUST MASTER to get started in data science.
With the plethora of information online, it's immensely unmotivating, overwhelming, and perplexing to navigate a huge list of resources without any context for how they fit together, why they matter, or how they will help you get a data science job.
Do you really need to know statistical learning theory and functional analysis at a graduate school level to get a data science job?
You end up spending more time debating what to learn than actually making progress.
Given your specific educational background and work experience, you still don't know what knowledge gaps you have, which you need to close, and which you can ignore.
A data science job (with its high profile and lucrative salary) seems more and more out of your reach with each passing day.
You wish someone would put you our of your misery by telling you specifically what you need to learn (down to the specific key words and topics), how to put together your data science portfolio, and how to best write your resume to become a data scientist.
How would you feel if you woke up tomorrow with perfect knowledge for how to become a data scientist as fast as possible?
You would be 100% confident on which MOOC's to take, which books to read, and which statistical programming libraries to use.
You'd know the highly specific knowledge gaps you must close given your educational and professional background.
Every data science project you completed would make hiring managers sit up and notice due to your topic choices, how you communicate, and what you accomplished.
Your resume would be at the top of the 'must-talk-to-candidates' pile for every data science job you applied to.
Your money, time, and effort would be spent wisely and to great effect in attaining your dream data science job.
You'd be motivated, sure, and enthusiastic about having the right data science position within your reach.
Done are the days of sitting at a table being surrounded by books on books on books and endless amounts of data science resources.
Each guide will introduce you to tons of fail-safe processes you can follow to the letter that will help you get that data science job as fast as possible.
How to figure out the knowledge gaps that MUST be closed in order for your to become a data scientist
How to develop your perfectly personalized 'learning data science' action plan
How to work backwards from a data science job to your current situation to build your plan
How to build the right data science skill sets from day one so that you don't waste time or effort
The Get A Data Science Job Course will direct you in constructing your own highly personalized plan for what you need to learn and what you can safely ignore - saving you time, effort, and worry.
And most importantly, the Get A Data Science Job Course will give you the straight truth of what matters and what you can ignore to achieve your dream of becoming a data scientist with a high profile and lucrative salary faster than you've ever imagined.
It will be like future you (an awesome data scientist) travelled back in time to tell current you all the right things to do and focus on.
- On Thursday, October 17, 2019
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