Artificial Intelligence

MACHINE LEARNING WITH PYTHON

Course Description

Machine Learning with Python is the new arenaof modern Artificial Intelligence; Machine Learningis new trend in Information Technology. We here at Codec Networks will ensure that you are not leftbehind in this fast moving world of Big Data and its uses in sense of Analytics and developing models in Machine Learning, and help get started in this field.

We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course isfun and exciting, but at the same time we dive deep into Machine Learning. Enroll with Codec Networks course to get started with Machine Learning.

Who Should Attend

This course is intended for learners who have basic python or programming backgroundand wants to apply machine learning, supervised learning, unsupervised learningand text analysis techniques to gain new insight into data. The class is taught in a tutorial format using the pandas library. Only a minimal statistics background is expected and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in Machine Learning will still find the skills they acquire in these courses valuable in their studies and careers.

Modules Covered

  • Introduction to Data Analytics with Python.
  • Python Essentials
  • Scientific Distribution used in Python for Data Science
  • Accessing/Importing Data and Exporting Data using Python modules
  • Data Manipulation-Cleaning & Munging using Python modules
  • Data Analysis-Visualization Using Python
  • Introduction to Statistics
  • Introduction to Random Forest Algorithm and how it is used?
  • Data Exploration for Modelling.
  • Data Preparation
  • Unsupervised Learning: Segmentation-Solving Segmentation Problem
  • Linear Regression Introduction and Applications.
  • Logistic Regression: Solving Classification Problems
  • Machine Learning - Predictive Modeling Introduction to Machine Learning & Predictive Modeling.
  • Bayesian Networks
  • Supervised Learning Decision Trees - Introduction - Applications
  • Support Vector Machine -SVM Motivation for Support Vector Machine & Applications
  • Text Mining and Analytics
  • Project

Course Duration

  • Fast Track: : 10 Days (8 Hours/Day)
  • Regular Track: : 8 Weeks (2.5 Hours/Day)
  • Weekend Track : 12 Weekends (3 Hours/Day)

Post Training Program (CODEC Networks Specialty)

  • Project Work
  • Extensive Classroom Training
  • Internship Opportunity with experts and R & D team
  • Placement Assistance **
  • Discount Vouchers up to 10 - 15% for further training

Package Includes

  • Weekly Assignments, Reference codes & Study material in PDF format
  • Module-wise Case Studies/ Projects
  • Career Guidance & Career Support
  • The completion of some selected assignments & case studies
  • Training certificate from CODEC Networks

Course related details

  • DATA SCIENCE WITH PYTHON flyer

    View FLYER for this Course

Course related details

  • Pre-Course Technical Evaluation
  • Hand-Over Labs & Practical's Checklist for Review
  • Classroom Evaluation Tests
  • Candidate Wise Reporting & Post Assessment
  • Certificate of Excellence from Codec Networks
  • Live Project Work

Contact us

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