Científico de datos
340 Hours / 8 Months, Part Time Program
This part-time Data Science program features expert instruction, hands-on projects, AI-driven analytical methodologies, 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. Crucially, our program integrates the use of advanced Artificial Intelligence tools in the training process. This empowers learners to understand and apply AI-driven analytical methodologies, effectively harnessing the power of data to extract valuable insights and make data-driven decisions.
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.
Abrir puertas con conexiones industriales
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 empresas líderes del sector para que nuestros programas respondan lo mejor posible a las necesidades de la industria local, garantizando que los graduados estén preparados para trabajar en cuanto terminen el programa.
Guiar a los estudiantes para que realicen un proyecto profesional
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.
¿A quién va dirigido el programa?
Individuals with some math skills and prior experience in programming, who aspire to launch a career in Data Science.
Profesionales de primera categoría
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
Director General de Wawiwa
Eran es un emprendedor de la educación tecnológica con más de 20 años de experiencia. Eran fundó y dirigió cuatro empresas de formación en TI: Formación John Bryce (Israel), TRIG (China), JB-IQsoft (Hungría), KocBryce (Turquía). Eran también se asoció para establecer DAN.IT Educación (Ucrania), Techub (Georgia), etc. Además, Eran dirigió Mentergy, que ofrece soluciones de aprendizaje electrónico y a distancia. A lo largo de los años, fue responsable de la reconversión profesional de más de 50.000 personas que ahora trabajan como profesionales de la tecnología.
Daniel Anderson
Jefe de Formación
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
Jefe del Programa de Científicos de Datos
Program Curriculum
- Python and Data Science introduction
- Data types
- Control structures
- Funciones
- 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
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