Educational Institutions Training

Overview

The field of Information Technology is ever growing and changing. New technologies are being developed every day to ease the work in different business domains and to help businesses make better decisions. This is the era of data analytics and it has changed the business scenario altogether. Every business/organisation is opting for these innovative methods using data analytics to have a competitive edge in the market. But at the same time, it has become a challenge for the young students as well as the faculty members to keep themselves up-to-date with all these new technologies. We, at Emerging India, are here to assist the educational institutions in achieving this goal.

Emerging India, a proud member of NASSCOM and a Licensed Training Partner of NASSCOM in data analytics, plays an important role in providing the young students and the teaching faculty, training in cutting-edge technologies like R, Python, SQL, Statistics, Machine Learning, Big Data Hadoop & Spark, Digital Marketing, Data Visualization through Tableau and Advanced Excel.

For educational institutions, Emerging India has an offering of a range of programs/courses such as Student Development Programs, Faculty Development Programs, Soft Skills Programs, Induction Programs on Data Analytics and NASSCOM Full Stack Data Analytics Program.

We help Colleges and Institutes by training their students in cutting-edge technologies like Hadoop, Spark, Machine Learning, ,Digital Marketing Advanced Python and R.

Skills to Learn

  • Data Analytics
  • Hadoop
  • Spark
  • Machine Learning
  • Digital Marketing
  • Advanced Python and R

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Offerings under Educational Institutions Training

STUDENT DEVELOPMENT PROGRAM

STUDENT DEVELOPMENT PROGRAM: We can conduct the Student Development Program in your premises related to Data Analytics/Statistics/Artificial Intelligence/Machine Learning etc. as per given curriculum. We have divided the curriculum into five different modules, you can pick and choose as per your requirements. We have also partnered with many colleges for SDP on Data Analysis using Software Packages. A paid workshop for 5 days (07 hours per day of training) on Big Data Analytics covering the following topics

Big Data Analytics Customized Modules

Target Audience: B.Tech , BSc(Statistics), BCA, MCA & MBA Graduates

A workshop for 5 days (07 hours per day of training) on Big Data Analytics covering the following topics

Module-01(Day-01)

S NO.TOPICInstallation RequiredDuration
1Introduction to R ProgrammingR, R Studio1 hour
2Data Structures of R- vectors, matrices, arrays, data frames, lists.2 hour
3Control Structures1 hour
4Apply Family- Sapply, Tapply, Mapply, apply2 hour
5Visualization in R1 hour

Module-02(Day-02)

S NO.TOPICInstallation RequiredDuration
1Introduction to Python ProgrammingPython, Anaconda1 hour
2Data Structures of Python- List, Tuples, Dictionary, Sets, matrices, arrays, data frames2 hour
3Control Structures1 hour
4File read/write in Python1 hour
5Visualization in Python2 hour

Module-03(Day-03)

S NO.TOPICInstallation RequiredDuration
1Introduction to Machine LearningR, R Studio1 hour
2Supervised machine learning algorithm- Classification4 hour
3Unsupervised Machine Learning algorithm- Clustering1 hour
4Application of Machine Learning1 hour

Module-04(Day-04)

S NO.TOPICInstallation RequiredDuration
1Introduction/ Architecture to HadoopHadoop1 hour
2HiveHive2 hour
3PigPig1 hour
4HbaseHbase1 hour
5Sqoop/FlumeSqoop/Flume2 hour

Module-05(Day-05)

S NO.TOPICInstallation RequiredDuration
1Architecture of SparkHadoop1 hour
2ScalaHive2 hour
3Spark SQLSpark SQL1 hour
4SparkRSparkR1.5 hour
5PySparkPySpark1.5 hour

FACULTY DEVELOPMENT PROGRAM

We can conduct the Faculty Development Program in your premises related to Data Analytics/Statistics/Artificial Intelligence/Machine Learning etc. as per given curriculum. We have divided the curriculum into five different modules, you can pick and choose as per your requirements. We have also partnered with other DU colleges for FDP on Data Analysis using Software Packages. A paid workshop for 5 days (07 hours per day of training) on Big Data Analytics covering the following topics

Module-01(Day-01)

S NO.TOPICInstallation RequiredDuration
1Introduction to R ProgrammingR, R Studio1 hour
2Data Structures of R- vectors, matrices, arrays, data frames, lists.2 hour
3Control Structures1 hour
4Apply Family- Sapply, Tapply, Mapply, apply2 hour
5Visualization in R1 hour

Module-02(Day-02)

S NO.TOPICInstallation RequiredDuration
1Introduction to Python ProgrammingPython, Anaconda1 hour
2Data Structures of Python- List, Tuples, Dictionary, Sets, matrices, arrays, data frames2 hour
3Control Structures1 hour
4File read/write in Python1 hour
5Visualization in Python2 hour

Module-03(Day-03)

S NO.TOPICInstallation RequiredDuration
1Introduction to Machine LearningR, R Studio1 hour
2Supervised machine learning algorithm- Classification4 hour
3Unsupervised Machine Learning algorithm- Clustering1 hour
4Application of Machine Learning1 hour

Module-04(Day-04)

S NO.TOPICInstallation RequiredDuration
1Introduction/ Architecture to HadoopHadoop1 hour
2HiveHive2 hour
3PigPig1 hour
4HbaseHbase1 hour
5Sqoop/FlumeSqoop/Flume2 hour

Module-05(Day-05)

S NO.TOPICInstallation RequiredDuration
1Architecture of SparkHadoop1 hour
2ScalaHive2 hour
3Spark SQLSpark SQL1 hour
4SparkRSparkR1.5 hour
5PySparkPySpark1.5 hour

SOFT SKILLS TRAINING PROGRAM

S NO.Topics to be coveredDuration Of classTotal Duration of class
1Introduction to Soft skills2 hours
2Manage your work to requirement8 hour
Time Management2 hours
Time management aspects2 hours
Four Quadrants of Time2 hours
Work Management & Prioritization summary2 hours
3Work effectively with Colleagues10 hours
Team work2 hours
Team Building Fundamentals2 hours
Team Development2 hours
What is Professionalism/what/why2 hours
Exhibition of Professionalism2 hours
4Maintain Healthy and Safe Work Environment10 hours
Health, Safety and Security2 hours
Accidents and Emergencies2 hours
Work place Safety2 hours
Work place safety Guidelines /Rules2 hours
Handling Accidents /case studies2 hours
5Information In Format Standards10 hours
Knowledge Management2 hours
Importance of KM2 hours
Knowledge Items2 hours
KM framework2 hours
Summary2 hours
6SELF SKILLS10 hours
Dream Building2 hours
Goal setting2 hours
Attitudes and Techniques for Success2 hours
Emotional intelligence2 hours
Inter personal skills2 hours
7COMMUNICATION SKILLS10 hours
Diction and correct pronunciations2 hours
Verbal Communication Skills2 hours
Written Communication Skills2 hours
Non-Verbal (Body Language) Communication Skills2 hours
Listening skills2 hours
8Develop skill and Competencies10 hours
Positive Attitude2 hours
Understanding work culture2 hours
Conflict management2 hours
Ethical behaviour2 hours
Image building2 hours
9INTERVIEW SKILLS12 hours
Choosing a career2 hours
How to hunt for a job2 hours
Making great resumes/design2 hours
Power dressing/creating impression2 hours
Body language at interviews2 hours
Facing Group discussions2 hours
10OFFICE SKILLS10 hours
Understanding Corporate culture2 hours
Meetings and Mannerisms2 hours
Performance Presentation skills2 hours
Team Building with colleagues2 hours
Business Correspondence2 hours

120 HRS PROGRAM MODULE

Structured Programming Language-10 hours

What is a Database?
Types of Databases
Data Definition Language (Create, Drop, Truncate)
Data Manipulation Language (Insert/Update/Delete)
Joins (Inner, Outer, Left outer join, Right outer join)
Highest, lowest, nth highest, rank
Transposing data
Nested Queries
Assignment
Assessment

R Programming – 12 hours

R Programming – 12 hours
Introduction to R programming
Vector, Matrix, Array
Data Frame, List
File Handling in R
Connecting database with R
R Inbuilt functions / User defined functions
Apply Family (sapply, lapply, tapply, mapply, apply)
Visualization in R (ggplot, plot, line, bar etc)
Assignment
Assessment

Python Programming – 12 hours

Introduction to Python programming
List, Tuple, Dictionary, Set, String, Number
Regular expressions in Python
File Handling in Python
Connecting database with Python
Numpy
Pandas
Visualization in Python(matplotlib)
Assignment
Assessment

Statistics – 8 hours

Measures of Central Tendency
Measures of Variation
Kurtosis and Skewness
Hypothesis Testing
Covariance and Correlation
Simple Linear Regression Analysis
Multiple Linear Regression Analysis
Simple Non-Linear Regression Analysis
Multiple Non-Linear Regression Analysis

Machine Learning – 18 hours

What is Machine Learning
Types of Machine Learning
Supervised, Unsupervised, Semi-supervised, Reinforcement Machine Learning
Training, testing data set, Confusion Matrix, ROC curve, k-fold validation test
KNN Classification
Artificial Neural Network classifier
Naive Bayes Classifier
Decision Tree
Time Series Analysis
Clustering
Assignment
Assessment

Hadoop/Spark-18 hours

HDFS Architecture/ Commands
HIVE Architecture
HQL
No SQL Database-HBase
PIG
Flume/Sqoop
Spark
SparkSQL
PySpark/SparkR
Assignment
Assessment

Tableau – 10 hours

Tableau Desktop
Dimension/Measures
Filters
Dual Axis
LOD Expressions
Extract/Live Connections
Maps, Market Map, Bubble Chart
Assignment

Excel/Word – 12 hours

Filter/ Sort/ Conditional Formatting
Referencing
Arrays, Vlookup, Hlookup
Match, Index, What if Analysis
Excel Functions
VBA
Graphs
Word Headings
Table/ Image/ Text formatting
Assignment
Assessment