Data Science & Machine Learning with Python & R

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Data Science & Machine Learning with Python & R

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    Data Science & Machine Learning with Python & R

Course Overview

This course will equip students with in depth knowledge and understanding in R & Python. Candidates will have a solid grasp on Data Cleansing, Data Manipulation, Data Integration, Data Wrangling, Missing data & Imputation, Visualization, Supervised and Unsupervised Machine Learning algorithms and their implementation by the end of this course

Course Objective

  • Providing experience in working with real-time applications of Data Science & Data Analysis
  • To make the learner identify potential zones of uses of Data Science & ML
  • Acquaint the learner to easily land up in the job role of either Data Scientist, Data Analyst, Business Analyst in IT Industry

Course Outcomes

  • Should be able to apply the concepts learnt in R, Python & ML on the job and real time projects
  • Have a detailed understanding of all the machine algorithms, their usage and application in different domains / industry verticals
  • Land up into a job role of Data Analyst or Data Analyst.
  • Switch careers in the field of Data Science & Machine learning with an average hike of 30%

Projects

  • Webs scrapping top 100 movies at IMDB website and perform EDA
  • Twitter Sentiment Analysis Data Wrangling,
  • Data Imputation, missing data & Visualization of HouseVotes84 data
  • Using Association rule mining to identify " Customer buying pattern"
  • Using Clustering Algorithm to diagnose " Breast cancer"
  • Identify Political affiliation from voting patterns using Naïve Bayes
  • Filtering mobile phone spam using Naïve Bayes classification
  • Predict Titanic survivor using Logistics regression
  • Predict Customer churning in Telecom data set using Decision tree
  • Identify risky bank loans using C5.0 Decision treee algorithm
  • Applying Random forest for Sonar data
  • Wikipedia pageview anomaly detection
  • Computing confusion matrix & drawing ROC + AUC curve using HouseVotes84 Data
  • Simple Linear Regression for Australian Athletics data
  • Simple Linear Regression for Australian Athletics data
  • Predicting Medical expenses using Linear Regression
  • Forecast tractor sales through Time Series & ARIMA Models

Study Material

  • PPT’s
  • Practice Questions
  • Assignments
  • Reading Material / Books in soft copies
  • Projects
  • Recorded sessions on LMS
  • Worked upon scripts on R & Python

Suggested Job Profile after taking the course

After completion of the course, the candidate can take up one of the below job profiles

  • Data Scientist
  • Data Analyst
  • Business Analyst
  • Data Science Associate
  • R& D Professional
  • ML Engineer
  • Data Engineer etc

Software Tools & Details

Download Full course curriculum:

Why Choose Us?

Intiglide has been formed by a cohesive group of professionals with more than a decade of experience in the industry and coming from reputed institutes like IIM’s, XLRI Jamshedpur, IIIT and IIT. The course has been developed FOR THE INDUSTRY, BY THE INDUSTRY. The course focuses on the application of Data Science and Machine Learning algorithms on real time cases. It is completely Live, Interactive and Hands on..


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