Strategic Workforce Planning
Strategy & Data Driven Decision Making
Measuring Performance & Potential
Financial HR – Part I
Financial HR – Part II
Costs of Absenteeism
Understand how to pick a problem that is relevant
Explain how you can measure an outcome
Understand how to check data for errors
Comprehend how to clean HR data
Understand how to speed up your Excel worksheets
Comprehend how to create new research questions based on the data
Utilize trend lines in charts
Statistics in Excel
Tables in Excel
CBuilding your First Dashboard
Dates in Pivot Tables & Dashboards
Introduction R/R-Studio - GUI
Concept of Packages - Useful Packages (Base & other packages) in R
Data Structure & Data Types (Vectors, Matrices, factors, Data frames, and Lists)
Importing Data from various sources
Database Input (Connecting to database)
Exporting Data to various formats)
Viewing Data (Viewing partial data and full data)
Variable & Value Labels – Date Values
Data Manipulation steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type converstions, renaming, formating etc)
Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
R Built-in Functions (Text, numeric, date, utility functions)
R User Defined Functions
R Packages for data manipulation(base, dplyr, plyr, reshape,car, sqldf etc)
Introduction exploratory data analysis
Descriptive statistics, Frequency Tables and summarization
Univariate Analysis (Distribution of data & Graphical Analysis)
Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis)
Creating Graphs- Bar/pie/line chart/histogram/boxplot/scatter/density etc)
R Packages for Exploratory Data Analysis(dplyr, plyr, gmodes, car, vcd, Hmisc, psych, doby etc)
R Packages for Graphical Analysis (base, ggplot, lattice etc)
Doing Analytics on Data
Introduction to Tableau Desktop
Tableau Desktop Interface
Connecting Data Sources
Organizing and Formatting Data
Create Dashboards and Stories
|HR Grievance Handling System|
|Labor Welfare Activities And Safety Measures.|
|Performance Appraisal System (PAS).|
|Employees Satisfaction Survey|
Learn from our comprehensive collection of project case-studies, hand-picked by industry experts, to give you an in-depth understanding of how data science moves industries like HR, telecom, transportation, e-commerce & more.
|You will be having the opportunity of 10-15 Hrs e-learning exercises along with instructor-led-training which enable candidates to get the maximum out of the subjects and empowering them to build logics to hand any new requirement.|
This program has been designed in collaboration with some of the most influential analytics leader and top academician in data science.
Thanks to the digital revolution that is sweeping the world and India in particular, data scientists are now the most sought-after professionals by big corporations as well as startups. And companies across industries are rewarding good data analysts and scientists with desirable career growth and salaries.
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The field of data science is thriving as it is proving to be effective not just across industries but also across departments within organizations.
6 out of 10 developers are gaining or looking to gain skills in machine learning and deep learning.
Data scientists make around 75 Lakhs on average.
India alone will need around 2,00,000 data scientists by 2020
Our Participants are highly satisfied with the quality of training (on R and Python), course material (if applicable), and level of knowledge that the faculty has. We appreciate the way