Best Project Based 6 Weeks Data Science Summer Training Institute in Noida

Best Project based 6 weeks Summer Training on Data Science in Noida

4 out of 5 based on 23 ratings. 5 user reviews.

APTRON is the best Data Science 6 Weeks summer internship training company in Noida offers real-time and fully job-oriented live project based 6 weeks Data Science summer training in noida. Our 6 weeks certification course contains basic to advanced level knowledge, and this entire course is designed and developed to grab job opportunities in reputed MNCs.

APTRON’s 6 weeks Data Science training in noida based on live project aspirants learn the skills for Introduction to Data Science, Basic Data Manipulation using R, roles played by a Data Scientist, Machine Learning Overview, Understanding K-Means Clustering, Understanding the Process flow of the Supervised Learning Technique, Subscripting, Mahout Introduction and Algorithm Implementation, implementing Association rule mining in R. Our Data Science course on real time projects along with placement training. Our Training in noida has been designed as per latest industry trends and keeping in mind the advanced course content and syllabus based on the professional requirement of the student; helping them to get placement in multinational companies and achieve their career goals.

Our mentors are certified experts and highly experienced working professionals with hands on virtually multiple projects knowledge. We have structured our Data Science course content and syllabus as per student requirements to achieve their career goal.

APTRON is one of the biggest Data Science training centres in noida with world-class infrastructure and facilities and the opportunities of opting for multiple courses at Noida location. APTRON in Noida trains thousands of individuals for Data Science at affordable fee parameter that is fully customized keeping in view the training and course content as per the requirements of each and every attendee.

Data Science involves "Learning by Doing" utilizing the most contemporary infrastructure to execute hands-on exercises and real-world simulations. This comprehensive hands-on experience in Data Science course ensures that each and every learner grabs the technical knowledge and skills that he or she really needs to apply while at work after getting the job in MNCs.

APTRON's Project-based 6 Weeks Summer Training in Data Science Covers the Following Modules

Summer Training in Data Science is a modular 6 weeks course, regularized over 5 days a week, 2 hrs a day, and exclusively includes practical sessions. The course curriculum of Summer Training in Data Science comprises:

Course Content Covered in Data Science Training Course

Introduction to Data Science

Introduction to Big Data
Roles played by a Data Scientist
Analyzing Big Data using Hadoop and R
Methodologies used for analysis
The Architecture and Methodologies used to solve the Big Data problems

Basic Data Manipulation using R

Understanding vectors in R
Reading Data, Combining Data
Subsetting data
Sorting data and some basic data generation functions

Machine Learning Techniques Using R Part-1

Machine Learning Overview
ML Common Use Cases
Understanding Supervised and Unsupervised Learning
Techniques, Clustering
Similarity Metrics
Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models

Machine Learning Techniques Using R Part-2

Understanding K-Means Clustering
Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
Implementing Association rule mining in R

Machine Learning Techniques Using R Part-3

Understanding Process flow of Supervised Learning Techniques
Decision Tree Classifier
How to build Decision trees
Random Forest Classifier
What is Random Forests
Features of Random Forest
Out of Box Error Estimate and Variable Importance
Naive Bayes Classifier

Introduction to Hadoop Architecture

Understanding K-Means Clustering
Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
Implementing Association rule mining in R