Data Scientist

340 Hours / 8 Months, Part Time Program

This part-time Data Science program features expert instruction, hands-on projects, and a real connection to the industry to get graduates hired.

In the digital kingdom where web and mobile applications help us manage nearly every aspect of our lives, data is king. Every digital action is visible and trackable, enabling corporations to accumulate and analyze vast amounts of both personal and business data. The use of ‘Big Data’ is driving disruption in every field — from vehicle navigation, through medicine, to cybersecurity.

Over the last few years, new professions like Data Analysts and Data Scientists have appeared on the market. Their job is to make sense and create value from the ever-increasing amounts of data that has become available.   

Teach Students to Solve The World’s Most Interesting Problems

Students will become indispensable to employers with data science fluency. Graduates will harness the predictive power of data to work at the forefront of diverse industries like public policy, robotics, and FinTech.

Open Doors With Industry Connections

Equip students to succeed in a rapidly expanding field with help from our network of data experts, instructors, hiring partners, and alumni. The Data Science curriculum was created in collaboration with the industry’s leading companies to make our programs as relevant as possible to the local industry’s needs, assuring graduates will be job-ready as soon as the program ends.

Guide Students to Deliver a Professional Project

Throughout the program, practical skills are acquired through the completion of projects that tackle real-world data problems from end to end. Students will gain hands-on experience with statistical and machine learning models, Python programming tools, neural networks, NLP and more, compiling a portfolio of projects designed to reinforce what students have learned in each unit.

Who Is the Program For?

Individuals with some math skills and prior experience in programming, who aspire to launch a career in Data Science.
*Candidates don’t have a programming background? A 70-hour introductory program is available to close those gaps. Otherwise, all candidates take a computerized assessment to ensure that they have the right personality, as well as the basic math and logic skills, to complete the programs and be successful in their future jobs.

Top Notch Professionals

This unique program was built by a professional team made up of the leading experts in Data Science, with vast knowledge and experience in training too.

Eran Lasser

CEO of Wawiwa

Eran is a tech education entrepreneur with over 20 years of experience. Eran founded and managed four IT training companies: John Bryce Training (Israel), TRIG (China), JB-IQsoft (Hungary), KocBryce (Turkey). Eran also partnered to establish DAN.IT Education (Ukraine), Techub (Georgia), and more. In addition, Eran managed Mentergy, which provides e-learning and distance learning solutions. Over the years, he was responsible for the reskilling of more than 50,000 individuals now working as tech professionals.

Daniel Anderson

Chief Training Officer

Daniel is responsible for updating state-of-the-art topics in the company’s tech training programs, and for maintaining its training methodologies. Daniel was the Chief Trainer at the Israel Defense Force’s Tech Training Center and is a graduate of the IDF training process. He develops and delivers a wide range of programming courses, and is a Full-Stack Developer and D

Liran Ben Haim

Head of Data Scientist Program

Liran has over 25 years of programming and instruction experience. Over the years, he has developed and delivered tech programs in various areas, including data science, database systems, embedded systems, and more. Liran is the Co-CEO at Bina Software Development, a company delivering software projects to various organizations in the Israeli tech ecosystem. In addition, Liran is a co-founder and CTO at various startups.

Program Curriculum

  • Python and Data Science introduction
  • Data types
  • Control structures
  • Functions
  • Object-Oriented Programming
  • Modules and packages
  • Useful packages
  • Libraries Overview
  • Numpy, Scipy, Matplotlib
  • Data Understanding 
  • Data Preparation
  • Pandas and Seaborn
  • Modeling
  • Supervised Learning 
  • Unsupervised Learning
  • Validation
  • Tuning 
  • Tools
  • Scikit-Learn 
  • Tensorflow
  • SQL 
  • Hadoop and Spark
  • Cloud Notebooks 
  • Tools
  • Deployment
  • Deploying Web Apps and Services
  • Neural Networks 
  • Solving Complex Problems
  • CNN, RNN
  • Autoencoders
  • Deployment
  • NLP
  • Time Series 
  • Semi-Supervised
  • Reinforcement Learning