Do you identify as female? And are you interested to pursue your career in Machine Learning, Artificial Intelligence and Data Science? This course is for you!
Classes fromTo be announced
Graduation dayTo be announced
Apply now
Data is new fuel that’s driving decision making across organisations and Economic Times reported a 400% increase in demand for data science professionals across myriad industries at a time when the supply of expertise is witnessing a slow growth. Europe lacks massively when it comes to expertise in AI, ML, and Data Science. Do you still have an excuse to not start learning these in-demand skills? Struggling to find where to start learning from pool of resources available online!
Code to Change proudly presents Introduction to AI and ML using python as a 2.5 months bootcamp that is aimed to train women of Amsterdam who want to pursue their career in AI, ML and Data Science where one can get skills that helps them to get placed, upgrade their careers and start an own business in the domain.
A 10 Weeks Boot Camp to train you to become expert on subject.
The promotional fee for this course is 499 Euros only instead or 1500 Euros.
Depending on availability, we can sometimes offer limited number of scholarships available for students applying from Amsterdam Metropolitan Region. Please mention clearly if you fall in this region.
Interested? Take a look of our past programs in the Netherlands!
Training by experienced facilitators and industry consultants
Live chat support during the session and through discussion forums after the workshop
Live instruction in interactive mode
Everyday quiz and practice to test Check for understanding
Previous sessions available for review till the end of the workshop
Meet lead advisor
Dr. Didem Gurdur BrooAn experienced researcher who is trained as a computer scientist. She holds MSc in sustainable environment and energy systems and PhD degree in mechatronics. Currently, she is a research associate at the University of Cambridge at the Department of Engineering. Her current research interest is on data science for cyber-physical systems such as collaborative robots, autonomous vehicles and smart cities. She strongly advocates the importance of transdisciplinary, collaborative research.
Her research focuses on blending systems thinking, future studies and design thinking approaches to develop methods, methodologies and implementations for the purpose of overcoming interoperability, complexity and sustainability challenges related to cyber-physical systems. Dr. Didem Gürdür has been granted prestigious Marie Skłodowska-Curie Global Fellowship to conduct research on her own project on human-centred and sustainable cyber-physical systems at Stanford University starting from September 2021. She has been granted IEEE Senior Membership due to her significant performance and excellence over the last five years. She is a data champion of the University of Cambridge, a member of European AI Alliance, and mentor at Women in AI Ethics. She actively contributes to the discussions of all aspects of data, artificial intelligence and their impact on the society.
Meet course instructor
Raja Sekhar ThotaA graduate in Mechanical Engineering with 5 years of experience in EdTech delivering curriculum in STEAM(Robotics and Automation, Internet of Things, Game making and 3D printing) and consulting for IoT start-ups for prototype development. Worked on Artificial Intelligence and Machine learning projects which include NLP for analyzing situational reports from W.H.O. of COVID-19, Computer Vision for sketcher app, HR analytics, Conversational AI and Cognitive Intelligence for safe and secure banking transactions and Intelligent Environment Monitoring leveraging IoT and Machine Learning. Loves to explore the trends in technologies attending conferences and hackathons.
Presently pursuing masters in Big Data and Business Analytics handling projects in domain of Artificial Intelligence and Industry 4.0. My master thesis is focused on XAI in self driving cars.
Participation is simple! You just need the following:
