Q. Is Data Science an in-demand occupation?

A. Yes, and the future is bright!

Being a successful data scientist takes more than just knowing how to make sense of big sets of data. You also need to understand business issues and how to address them with analytical solutions.

  • Career Options with growing job opportunities in next decade
  • Data Science: Increasingly a Key Factor in Decision Making
  • Rise of unstructured data sources
  • Building in-house Data Science teams is priority for increasing numbers of organizations

Hence, extremely sought after.

“Over next 3 years, India will face a shortage of 2 lakh data scientists” - The Hindu

Data Scientists with around 5 years of experience earn 75 lakh pa compared to 5-8 lakh for engineers with same experience “ – Team Lease

Q. What makes the GreyAtom course superior to other programs?

A. We get asked this often. We believe we are different , in several key ways:

  • The GreyAtom program is special forces training for budding Data Scientist. Tough. Intensive. Rigorous, and most importantly it is an onsite program versus online. We truly believe that accelerated learning can happen in a co-located agile environment with collaboration.
  • You progress through lessons only by writing code that meets requirements established by our curriculum. Every line of code you write is published to GitHub, thus adding to your Tech profile. No certificate or degree can prove you can code, but a great portfolio can!
  • As part of the curriculum, we are covering the entire spectrum of the Data Science landscape to make you a true blood Full Stack Data Scientist

Q. Is there Placement assistance?

A. Yes

We will work insanely hard to provide you with a great data science learning experience & mentoring .GreyAtom Career Team offers valuable tools and coaching before, during, and after the course to help students achieve their individual goals. There are one-on-one meetings with your Career Advisor, exposure to industry experts via our in-class Speaker Series, workshops focused on resume writing, LinkedIn, salary negotiations, mock technical interviews with professional data scientists, and moreCount on our career services to work closely with you from day 1 of the program to day 1 of your Job!"

Q. Is it more important to have a background in Python or statistics?

A. No

Some experience in both programming and statistics are necessary. Further background in either one is helpful but not critical for this course. Students jump into solving problems directly, which requires the use of Python skills and statistics knowledge together. You will learn more in the area you’re currently weaker in (if that applies to you), meaning that you will graduate from the bootcamp feeling strong and qualified in both.

Q. What tools will be used in the course?

A. Industry relevant only

You will build a strong foundation in the Python language, the unix/linux command line, machine learning packages such as scikit.learn, other statistics modules including scipy and pandas, web scraping packages like BeautifulSoup and Selenium WebDriver, PostgreSQL and mongodb databases, collaborative coding under version control with git, working on remote cloud servers such as rackspace, custom visualization tools, especially matplotlib and d3.js with support in HTML, CSS, JavaScript, and web hosting.

You will also learn about, and become familiar with, distributed algorithm frameworks such as Hadoop/MapReduce, system architectures with multiple servers of different roles, and web app frameworks such as Django.

Q. I want to have something concrete to show potential employers. What will I build during the course?

A. Build 4 data science projects throughout the course.

At the beginning, you follow along with the instructors as they guide you, but as you learn more, your control over each project increases. You soon make your own choices when tackling data science problems, and with each project, you get concrete, sharable results like blog posts, graphs, and/or reports. For each of these projects, you will conclude with a story of what the problem was, how you approached it, how you solved it, and what the results look like. The final captone project is your passion project, during which you have full control from start to finish. You will complete four data science projects throughout the course. Aside from giving you hands-on experience and confidence, these projects provide you with stories and outcomes as a great way to demonstrate your abilities to potential employers.

Q. Whom will I be sitting next to in this course?

A. Diverse yet mission focused.

  • Individuals who have a strong interest in manipulating large data sets, finding patterns in data, and making predictions.
  • Software developers who want to solve problems that involve large data sets, such as predicting user behavior on their website, making decisions, or the best way to classify content.
  • Individuals with a good grasp of programming, a solid knowledge of statistics and probability but missing the intersection of them both.

Q. Are there any prerequisites?

A. Yes

We would love to see these qualities in you - curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature. A good grasp of college-level statistics and probability and familiarity with a programming language would be an add on

Q. Are financing options available?

A. Yes

For Sure! We have tied up with loan providers like Credila so that there are no barriers for your knowledge!

We work with lending companies including Credila who understand the investment you are making in yourself. After applying to GreyAtom, you will receive details on how to get pre-approved with a lending partner and work with our Admissions Team to explore solutions to fund your tuition.

Scholarship offered for Women in Technology Leadership, Scholarship for Data Science Scholar.

Q. What do I need to bring to the bootcamp?

A. 3 things only ... 😄

You will need your computer, your brain, and a readiness to learn. Your computer needs to run OS X and have at least 4GB RAM, 2GHz, and a 100 GB HD. Alternatively, if you are a Windows user and your computer is fairly powerful, you could run a Linux Virtual Machine inside your normal Windows install. This requires some configuration.

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