Rutgers Data Science Curriculum

Rutgers Data Science Bootcamp teaches highly applicable skills for data analysis and visualization that can benefit professionals and companies in any industry.

It’s a fact: Companies care about what you can do, not what you say you can do. For that reason, our curriculum teaches you how to put what you’ve learned to work on real-world data analysis projects, from visualizing bike-sharing data in New York City to mapping earthquakes worldwide in real time. Our students learn how to navigate, engineer, and translate complex data systems into useful resources that employers need.

Data Science & Visualization

Module 1: Excel Crash Course Weeks 1-2


Description:

Learn to do more with Microsoft Excel! This module covers advanced topics like statistical modeling, forecasting and prediction, pivot tables and VBA scripting. You will even learn how to model historic stock trends – and, hopefully, how to beat the market!

What You Will Learn:

  • Microsoft Excel
  • VBA Script
  • Statistics Modeling

Module 2: Python Data Analytics Weeks 3-9


Description:

Gain a solid foothold in one of today’s fundamental programming languages. You’ll develop proficiency in core Python; data analytic tools like NumPy, Pandas, and Matplotlib; and specific libraries for interacting with web data, like Requests, BeautifulSoup, and Tweepy.

What You Will Learn:

  • Python, APIs
  • JSON, NumPy
  • Pandas, Matplotlib
  • Beautiful Soup, Tweepy

Module 3: Databases Weeks 10-12


Description:

Dive deep into the most prolific database languages: SQL and NoSQL. Work with MySQL and MongoDB to organize data into well-structured, easily retrievable formats.

What You Will Learn:

  • SQL
  • NoSQL
  • MySQL
  • MongoDB

Module 4: Web Visualization Weeks 13-19


Description:

Building visualizations is of little benefit without a way to communicate the message. In this module, you’ll learn how to use the core web development technologies (HTML, CSS, and JavaScript) to create new and interactive data visualizations that you can share with everyone on the web!

What You Will Learn:

  • HTML, CSS
  • JavaScript, AJAX
  • D3, Leaflet

Module 5: Advanced Topics Weeks 20-23


Description:

By program’s end, you’ll be immersed in new and in-demand topics like Tableau, Hadoop, and Machine Learning.

What You Will Learn:

  • Tableau
  • Hadoop
  • Machine Learning

Module 6: Final Project Week 24


Description:

As part of a small team, you’ll draw upon everything you have learned in the program to create an impressive data visualization application. Get creative and come up with something cool to show off to the whole world!

What You Will Learn:

  • Dreaming up something fantastic and pushing the bounds of reasonable and achievable

 

 

5 Key Skills of a Data Scientist

If you’re thinking about moving into the booming field of data, don’t be caught off guard when considering what skills you should have under your professional tool belt. Since data science is a newly celebrated territory, here are a few key skills to help clarify what you’ll need to be successful in the field. You can also check out our post on the Top 5 Resources for Aspiring Data Scientists to see the type  of tools data scientists can use for help.    The ability and desire to solve problems and think analytically. If you don’t have intellectual curiosity, then the field of data science might not be for you. Many people might think joining this field solely for the moolah could be the ticket to a life of luxury, but if you’re not passionate about intellectual expansion and critical thinking, then you should cross data science off your list of potential careers. Finesse in the communication department. Once you’ve learned the jargon, you’ll quickly realize that your non-data science colleagues aren’t quite able to speak your language. Being able to translate technical information into non-technical terms is crucial to efficiently create solutions to problems while working with a team.   You think like a data scientist. Employers look for individuals who maintain higher-level thinking and are able to see beyond the problem itself. Don’t be surprised if you’re asked data-driven problems during an interview. A skilled data scientist will have intuition about which data sets are important and which pieces of information will be useful for coming to an insightful, concise solution. Data ScienceBasic understanding of mathematics and statistics. As a data scientist, you’ll have to analyze and interpret large sets of data. More importantly, your analysis will be used to determine what to do with the data and which techniques you should (or should not) use to approach the problem. You have a keen eye for details. Data science isn’t a “that’s good enough,” sort of profession. You’ll be sifting through lots of tedious bits of information, and many times the data can be messy or difficult to work with. It’s incredibly useful to be able to spot imperfections in data and then correct it.   Afraid you’re lacking in one of these areas? Don’t worry. Each skill will continue to strengthen with practice and an ambitious attitude. While data science requires a multitude of other, more technical skills (see our data science curriculum for more information) having these core competencies can put you well on your way to landing the dream job or that promotion.
5 Key Skills of a Data Scientist

Our Guide to Conducting a Successful Job Search

You’ve worked your tail off to get to this point, but you realize you don’t even know where to begin. Starting a new job search is intimidating and overwhelming to say the least, but believe it or not, there are right and wrong ways to go about it. We’ve come up with a few pointers to help get you one step closer to landing your dream job.     Tip #1: Instead of mass-applying to companies on job search websites, look a little deeper into the company and try and get in touch with a real person. While job search engines like Monster.com or Indeed are plenty helpful, they might not necessarily be the best way to get seen. Many times, the one-click apply means your resume gets filtered through the system and might never be seen by an actual human. If you find a position on one of the many job sites, dig a little deeper. Go to the company website or LinkedIn page and look for the email of a real person. Many times, the department heads and HR manager are listed with their contact information. Though this still doesn’t guarantee you a response, there’s a better chance your email will be seen by the eyes of someone who might be able to pass it along to where it needs to go. If you can’t find an email, try to find the name of the HR or hiring manager, and personally address your email and cover letter to them. Tip #2: Try to strategically set up your interviews and go on lower-level interviews first to work your way up. There’s nothing worse than going in for an interview for the perfect job and then realizing you’re not prepared for the hard-hitting questions they might ask you. Your technical interview skills might be a little rusty or non-existent, so set up a couple of lower-level job interviews before you head toward the more ambitious ones. These more basic interviews will give you a chance to figure out how to sell yourself, which questions to ask, and the opportunity to build up your confidence. By saving the harder interviews for later, you give yourself the chance to unlock more difficult interview questions so you have the right answers for when it matters most. Tip #3: Never stop practicing your trade. Ever. Yes, you might be done with your coding boot camp, but you’re never done learning. During the job search process, you should continue practicing every chance you get. If you don’t have the answers to the questions you might get asked during an interview, you probably won’t be getting the job. If you don’t have a perfect understanding of something, take the time to study it until you do. There are plenty of (free) resources on the web to help you grasp and master difficult concepts. Employers want to be confident that you’re confident, so show them that you are! Tip #4: Don’t settle for anything you aren’t comfortable with. A classic rookie mistake when entering a new job market is thinking the first job offered should be the first job taken. Like we mentioned in tip #2, if you have your interviews prioritized, you most likely won’t want the first offer anyway. Know your worth. Make sure you do your research when it comes to the position that you’re seeking, and go into the job search with a ball-park of your ideal salary range. With more than 220,000 unfilled coding jobs, don’t be afraid to decline a position if it doesn’t satisfy your personal requirements. The job search process is tough. There are a lot of moving parts when it comes to making sure you’re ready for it, but don’t underestimate yourself. The process might seem daunting, but having the right tools will only yield the best result in the end. Take your time, put in the effort, and it will prove to be worth it. And when you attend Rutgers Coding Bootcamp, you won’t have to do the job hunt alone. Our career services team will guide you as you navigate the job search, getting you prepped along the way. Ready to find out more? Contact us today.  
Our Guide to Conducting a Successful Job Search

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