Data Science with Python Training

Data Science with Python Training with Certification

Course Description

Artificial Intelligence, Machine Learning, and Deep Learning are new trend in Information Technology we here at Codec will ensure that you are not left behind in this fast moving world of Big Data and its Use in sense of Analytics and developing models in Deep Learning, and help get started in this field.

Python is a general-purpose programming language that is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. Unlike any other Python tutorial, this course focuses on Python specifically for data science. In our Intro to Python class, you will learn about powerful ways to store and manipulate data as well as cool data science tools to start your own analyses. Enroll with Codec Networks course for starting your career in Data Science with Python

Who Should Attend

This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. The class is taught in a tutorial format using the pandas library, and 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 data science will still find the skills they acquire in these courses valuable in their studies and careers.

Modules Covered

  • Introduction to Data Science 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
  • Analysis-Visualization Using Python
  • Introduction to Statistics
  • Introduction to Predictive Modelling
  • Data Exploration for Modelling
  • Data Preparation
  • Segmentation-Solving Segmentation Problem
  • Linear Regression
  • Logistic Regression: Solving Classification Problems
  • Time Series Forecasting: Solving Forecasting Problems
  • Supervised & Unsupervised Learning
  • SVM & KNN
  • Supervised Learning NAIVE BAYES
  • Text Mining and Analytics
  • Project

Course Duration

  • Fast Track: : 5 Days (8 Hours/Day)
  • Regular Track: : 4 Weeks (2 Hours/Day)
  • Weekend Track : 5 Weekends (4 Hours/Day)

Post Training Program (CODEC Networks Specialty)

  • Live Project Work
  • Extensive Classroom Training
  • Internship Opportunity with experts and R & D team
  • Placement Assistance **
  • Discount Vouchers up to 15 - 25% 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