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Machine Learning Mini Bootcamp

Machine Learning Mini Bootcamp

  • About

    This mini bootcamp is a great opportunity to start a data science career. We are offering a FREE mini bootcamp to prepare you data scientist positions.

    This mini bootcamp will teach you Python basics and machine learning algorithms. During this mini bootcamp, you will explore a hands-on experience that ignites your enthusiasm, gain the confidence to learn data science.

    Your learning experience will be supported by office hours and a Slack channel, where you can ask your questions and get help when you got stuck.

  • Curriculum
    • Python and Jupyter Notebook Basics
    • What is Data Science?
    • Python Foundations
    • Setup the Jupyter Notebook
    • Introduction to Python with Jupyter Notebook
    • Linear Regression
    • Logistic Regression
    • Evaluating Model Fit
    • Data PreProcessing with Python
    • Feature extraction with Python
    • Support Vector Machines
  • Schedule
    • Start learning the Machine Learning with our convenient schedule!
    • The 5 weeks – 10 hours of schedule is as follows:
    • August 2-9-16-23-30
    • Sundays, from 10:00 am to 12:00 pm
  • Online

    Machine Learning Mini Bootcamp is now available online. Anyone who wants to attend this mini bootcamp can join online live webinars where the course content will be taught. Online sessions will be distributed through zoom conferences. Students will have access to the screen of the instructor and be able to ask questions through chat. You may attend this mini bootcamp no matter where you are.

  • Application

    The application process starts at magnimindacademy.com. You can view the course pages and learn more about your intended course. You can apply by clicking the “Apply Now” button and then fill out the application form.

  • Instructor

    Yasin Ceran is passionate about all things data and holds a vast experience in data analysis, mathematical modeling and Apache Spark, and in SQL, Python and R. Since 2013, he has been working at Santa Clara University as an assistant professor in the Information Systems and Analytics department (earlier Operations Management and Information Systems department), teaching applied machine learning, software platforms, and computer networks. He holds extensive experience in working on various data intense business platforms. Some of the notable projects he contributed to include the development of a predictive inventory allocation algorithm for Blockbuster with regard to the relationship between sales and customer reviews. Later, he created a mathematical model to capture the decision-making process of online customers based on their collection of data from different sources on the Web. He also developed a probabilistic model to detect churning users for Stumbleupon.com. Yasin is the proposer of an algorithm that helps to reduce bias in electronic formats. His present role involves working on optical DNA sequencing based on actionable big data.

    Yasin has completed his Ph.D. in Management Information Systems from the University of Texas at Dallas. He earned his M.S. in Electrical Engineering with a concentration in Telecommunications from the same university and obtained his B.S. in Electrical Engineering from Osmangazi Üniversitesi. At Santa Clara University, he also supervised a large team of software development students working on the Capstone Project. During his 5+ years of working experience, Yasin has worked rigorously on an array of data related projects encompassing data mining, statistics, big data, data science, and data visualization, and is dedicated to sharing his experience and expertise with learners. Apart from data science, Yasin’s knowledge spectrum also expands to cybersecurity and he is an ardent follower of innovative processes and implementations of technologies to defend the world’s digital economies.

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Comments / 2

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