This course provided to me a lot of invaluable tools to enter the ML/AI job market.
I did the course at age 30.
Before starting the course, I had around 4 years of experience in the Israeli hi-tech industry in Software related positions (Full-Stack Web/Product... Read More
I felt I lacked the practical and theoretical tools to apprehend the ML market and transition to a Machine Learning / Deep Learning position in the industry.
After considering options to transition and brainstorming with people in the industry / ITC alumni that shared their experience with me, I felt ITC Data Science Fellows track provided me the best value for time / investment to accomplish my goals.
Alternatives I considered were:
- studying online with Coursera, Udacity, Udemy and like
- taking a master's degress in CS / Statistics in a well-known university
- learn on the job slowly and hope to transition at some point to an ML position
Although I believe I could have acquired some of the tools provided by ITC with studying online / learning on the job, to me it felt would take too long to become proficient, and was lacking the significant advantage of being around teachers/mentors that are leading practitioners in the industry, with whom you can interact (ask questions, "best practices"), and a community of peers (that became great friends) that would work together on assignments, brainstorm best ways to solve problems.
A master's degree was out of scope because it involved too significant an investment of time and was less focused on industry.
Out of the many tools I got from this very intense 5-months experience, the ones I value the most are the numerous workshops organized by ITC partners that are industry leaders such as Outbrain, Taboola, SparkBeyond, Chorus, MobileEye (and much more), that provided opportunities to solve hands-on real-life data science problems (with real-life datasets, that you seldom find in toy problems from online tutorials) that involved the whole DS lifecycle: data acquisition, data cleaning / preprocessing, exploratory data analysis, feature engineering, data modelling (with both classical ML models and deep learning models) and data visualization in both NLP, Computer Vision and classical Machine Learning.
On top of the technical tools and frameworks to do proper data science work, the exposure to many companies in the Israeli ecosystem helped me map the options in the industry and understand well the different players in the ecosystem, and helped refine my job search strategy to what interested me most.
I am very glad about the personal project we did that allowed to practice an end-to-end NLP project in the domain of HR analytics, that involved Data Scraping from leading job boards, data cleaning and modeling with Topic Modeling (an NLP model), in order to identify clusters of skills relevant for specific job titles.
Last but not least, the part that was maybe the most significant to me was the project we did together with BMW company in the field of Satellite Imagery Analytics, which involved problems in the Computer Vision domain such as Object Detection, Classification and Semantic Segmentation.
The project involved data acquisition / exploration (around 40k instances), modeling and finally presentation of results to BMW Data Science leadership.
The modeling part involved Deep Learning frameworks such as Tensorflow Object Detection API, and PyTorch, using cutting-edge techniques such as Faster-RCNN, and SSD + VGG16.
The tools we used for this project (and were covered mostly during the course of the ITC training) are: pandas, scikit-learn, jupyter, matplotlib, Flask, Keras, Tensorflow, Docker, AWS EC2, AWS S3, Nvidia DIGITS framework.
If you feel I threw a lot of buzzwords in this review, and feel a bit lost with all of those, then you probably feel the same I did before taking ITC course.
I guarantee you that after taking the Fellows program, you will understand each and every one of those, and will know which part are they playing for the different tasks involved with Machine Learning / Deep Learning positions in the industry, and know how to combine them to create value from data.
I would probably have had little chance to reach my current position without the tools and exposure to the industry I got at ITC.
I am surely glad I got the chance to be part of this significant experience, and would recommend it warmly to anyone considering transitioning to the Data Science industry.
Thanks to ITC for the amazing initiative, and בהצלחה to you if you are considering entering this exciting journey :)