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Registrations are now closed for this course. Contact course coordinators if you wish to join the course.

Machine Learning: Fundamentals & Applications




OBJECTIVE OF THE COURSE:

Manufacturing industries are in the process of digitalization of their units and plants. Firms are interested in leveraging the data from the plants to gain insights on plant operations and make informed decisions based on it. The objective of the course is to provide fundamental understanding of data analytics and machine learning techniques for manufacturing and chemical process industries.

ELIGIBILITY CRITERIA:

  • There is no pre-requisite for any particular educational background. However, it is expected that the participants should have basic understanding of mathematical concepts
  • Experience in any programming language, preferably python is a plus but not mandatory.

  • COURSE FEES(INR):

  • Students (Bachelors, Masters, PhD scholars): 1500/- + 18% GST per person
  • Faculty, Postdoc: 3000/- + 18% GST per person
  • Industry Participants: 15000/- +18% GST per person
  • A special 10% discount for a group of 3 to 10 participants
  • Special Scheme for Academia (students, faculty and postdocs): Free registration for 1 participant with a group of 11 participants (including self) & 10% discount to all 10 participants + letter of appreciation to the institute/ department.

  • IMPORTANT DATES:

  • Registration starts on: 05-08-2023.
  • Registration closes on: 22-09-2023.
  • Course starting date: 23-09-2023.

  • Enrollment PROCESS:

  • Click Here to Sign-up with your Email
  • Provide Full Name, Email and Password to Sign-up
  • And OTP will be sent to your registered Email
  • Use that OTP to verify your Email address
  • Use your Email and password to Sign-in
  • For Individual enrollment, click on "Enroll For Course" page, for group of participants enrollment, click on "Group Enrollment" page
  • Select Department as Chemical Engineering.
  • Select Course as "Machine Learning: Fundamentals & Applications"
  • For individual enrollment, provide necessary details and click on button "Submit and Proceed to Pay"
  • If it is group enrollment, select number of participants and provide partcipants name and provide remaining details and click on button "Submit and Proceed to Pay"
  • Pay for the course through Payment Gateway and you will be successfully enrolled for the course

  • HAVE QUSTIONS? CONTACT US
    For any queries on the registration and course related matters contact:

    Dr. Venkata Reddy P
    Mob: 9940330878
    Email: venkat_palleti.che@iipe.ac.in
    Dr. Hemanth Kumar T
    Mob: 9445420495
    Email: hemanth.che@iipe.ac.in
    Prof. Seshagiri Rao A
    Email: seshagiri.che@iipe.ac.in




    Summary


    Course Status : Registrations Started
    Course Duration : 13 Weeks
    Course Timings : 2hours-Every Saturday (6.00-8.00 P.M.)
    Delivery Mode : Online (Cisco-WebEx Meetings)
    Level : Undergraduate/Postgraduate/Industrial
    Registration Start Date: 05 Aug 2023
    Registration End Date: 22 Sep 2023
    Classes Start Date : 23 Sep 2023

    Topics Covered


    No. of hours Topic and contents
    2 Introduction to Data science, Data analytics, Types of Data and Data analytics
    2 Descriptive Statistics: Frequency tables, Bar charts, Univariate and Multivariate Descriptive statistics
    2 Linear Algebra: Data matrix, Vectors, Matrices, Rank, Eigen values and Eigen vectors, Singular Value Decomposition
    2 Introduction to Machine Learning, Relation between AI, ML and DL, Approaches, Supervised, Unsupervised, classification, Function approximation, Machine Learning Workflow.
    2 Supervised Learning-Linear regression
    2 Supervised Learning-Logistic regression
    2 Unsupervised Learning: Use cases, K-means clustering
    2 Interpretability Analysis - SHAP, ALE
    2 Introduction to Python, Control structures, Functions, Pandas library, Scikit-learn library.
    2 Hands-on Session-Linear regression
    2 Hands-on Session-Logistic regression
    2 Hands-on Session-K-means clustering
    2 Capstone Project: Problem Definition, Description and Ideas to solve, Discussion