How to Accelerate Your Data Science Career

How to Accelerate Your Data Science Career

Posted by Pranjali Galgali

Updated: Mar 26, 2019

According to Wikibon, the global big data market is speculated to grow from $42 billion in 2018 to $103 billion by 2027. As companies strive to deliver cutting-edge, data-driven solutions, business practices and customer relationships have been rapidly evolving. With this, the value of data is rising quickly, as is the demand for highly qualified data scientists in all sectors.

Choosing a Data Science Bootcamp

Bootcamps are a great way to reinvent your career. In just three months, one gains Data Science skills with R, Python, Spark, and Hadoop, as well as the experience of using widely used industry tools such as Selenium, Caret, Tensorflow, AWS, and more. Bootcamps also prepare you for the real world, with immersive training, cutting-edge curricula, and one-on-one career support.

Why Choose NYC Data Science Academy?

According to Switchup, NYC Data Science Academy is one of the most reviewed and top-rated data science bootcamps. It is the only bootcamp which teaches both Python and R in addition to requiring each student to create a portfolio of four innovative capstone projects. The instructors go beyond programming fundamentals to teach students how to solve problems and gain critical thinking skills. The curriculum is constantly evolving to stay ahead of industry demands. If you are interested in becoming a data scientist, you can also attend our info session to find out more about the program and listen to our Alumni Panel.

About NYC Data Science Academy

NYC Data Science Bootcamps

Immersive Data Science Bootcamp: NYC Data Science Academy’s curriculum is focused on practical data science experience with heavy emphasis on machine learning algorithms, coding expertise, and database query. It encompasses over 400 hours of curriculum content including three hours of daily lectures in the morning as well as jump-start sessions in the afternoon. The next bootcamp starts on April 1, 2019.

Remote Intensive Bootcamp: NYC Data Science Academy’s remote intensive bootcamp is open to technology enthusiasts outside of the New York City area. It offers full-time, five days per week, live daily instruction, live communication, and real-world projects. Students also have access to prerecorded modules and over 1,000 coding questions for additional practice, as well as personalized job support. The next cohort starts on April 1, 2019.

Remote Part-time Bootcamp: This option provides lecture videos, slides, homework and solutions, code reviews, jump-start sessions, and a selection of guest speaker talks. We offer 4-month, 6-month, and 10-month options so students can choose a program that is of the right pace for them. Financing options and job-support is also available for remote part-time bootcamp students.

Subjects: Data Science, Data Visualization, Machine Learning, R Programming, Python, Hadoop, SQL, Git, Linux, Deep Learning with TensorFlow, NLP, Time Series

Locations: NYC, Online

Cost: $17,600.00 for any of these bootcamps along with full-funding options from Climb and SkillsFund.

Career Support

Students participate in presentations and job interview training to ensure they are prepared for top data science positions at prestigious organizations. NYC Data Science Academy also hosts networking and hiring event every quarter with more than 60 employers offering jobs. 93% of NYC Data Science Academy students are hired within six months of graduation.

Read all reviews here.


Pranjali Galgali

Pranjali Galgali is a Marketing and Communications Associate, NYC Data Science Academy. She is a Master's in Digital Media and Strategic Communications from Rutgers University. She enjoys reading and writing about data science, upcoming technologies and loves interviewing people.

View all articles

Topics from this blog: data science nyc data science academy Data Science News and Sharing Career bootcamp

Interested in becoming a Data Scientist?

Answer 3 Simple Questions and Get Immediate Course Recommendations.