TRAINING & INTERNSHIP ON PYTHON FOR DATA SCIENCE

  • 12000.00 Rs.
  • Published date: July 6, 2019
    • Gandhipuram, Coimbatore City, Coimbatore, Tamil Nadu, India [ Ad Id - 73547 | Ad Views - 13 ]

DEGREE : B.E, B.TECH, M.C.A, M.E, Ph.D, B.B.A, B.COM, B.SC, B.B.M, DIPLOMA, M.Phil 

LOCATION : Coimbatore

DURATION : 2 Months 


ABOUT COMPANY : PROMPT INFOTECH is a division of PITH Pvt Ltd, An ISO 9001:2015 certified company. We are one of India’s fastest-growing technology companies, delivering managed security services by safely embracing transformative technologies – cloud, mobility, Internet of Things (IoT), and others – through a unified, cloud-centric platform. Our Training & Development wing strives at updating niche technologies to technological aspirants all over the world through conferences / workshops / seminars & training.


DESCRIPTION :

Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.Professionally, Python is great for backend web development, data analysis, artificial intelligence, and scientific computing. Machine Learning is an intelligent technique which makes the software or application to recognize the vast data and determine the next course of action or task automatically by using some complex algorithms and set of predefined rules.


TRAINING MODULES :

Programming Basics - Python Data Types - Structures and conditional statements - Python core packages - Introduction to Jupyter Notebook - Introduction to Numpy and Pandas - Data filtering and selecting - Find duplicates and treating missing values - Concatenate and transform data - Basic Statistics and Exploratory Analysis - Descriptive summary statistics with Numpy - Outlier analysis - Overview of Supervised and Unsupervised Machine Learning - Linear Regression - Clustering with K-means - Naive Bayes Classification - Introduction to Neural Networks - Normalization vs Standardization of data - K-Nearest Neighbors (KNN) concept and application - Naive Bayes concept and application - Logistic Regression concept and application - Classification Trees concept and application - Hierarchical Clustering concept and application - Setting up the project with ML workflow. - Data Preprocessing and statistical exploration - Building , Training and evaluation of Machine Learning Model.

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