NASSCOM Certified Data Analyst

Data Analytics refers to the use of advanced data tools to analyse large volumes of Data to uncover patterns and connections and provide valuable insights to business leading to better decision making. Following are few examples from our everyday lives that shows the importance and the need for Data Analysis:

  • Companies like Ola and Uber use Big Data to analyze and predict the demand-supply gap. Based on this analysis, decision on surge pricing and fleet deployment are taken.
  • When booking flight and hotels online, companies track how many people are viewing flights or hotels for the same day. Based on this analysis, they tweak to price to maximize their revenue
  • Online portals like Amazon, Flipkart, Facebook, Google use analytics for better customer experience and services

The demand for Data Analytics professionals is growing at a rapid pace and is considered one of the highest paying professions.  To fulfil the current and future demand, NASSCOM has collaborated with leading analytics companies such as Accenture, Fractal Analytics, TCS, Cap Gemini and Wipro, to name a few, and created a program that will ensure learners are ready to be absorbed by these leading companies.

This program will help you master skills and tools like Clustering, Decision trees, R Studio, R Programming, Python, Big Data, Hadoop, Spark, SQL, NoSQL, Impala, Data Visualization tools like Tableau, Data modelling, Statistical functions, Machine Learning, deep learning algorithms that use predictive analytics to solve real-time decision-making problems.

The program provides access to high-quality content and other resources to put you on the right path to be a Data Analyst and eventually become a Data Scientist.

Course Outline

NASSCOM Certified Data Analyst is a 400 hour instructor led training covering data analytic concepts and hands-on learning. Each module is in accordance to the National Occupational Standards (NOS). These NOS specify the standard of performance individuals must achieve when carrying out a function in the workplace, and the knowledge and understanding they need to meet that standard consistently. The efforts of NASSCOM and Mr. Ashok Polapragada, Mr. Ranjit Kumar and Mr. Prakash Devarakonda at Karvy Analytics; Mr. Dwaraka Ramana K at First American; Mr. Amit Agarwal, Mr. Sidhartha Shishoo and team at Genpact; Ms. Snigdha Ray and Mr. Amit Sharma at ADP; Mr. Manoj Koundinya at Capgemini, and Mr. Ashish Mediratta at Wipro have gone into creating this industry aligned program. Our Data Analytics program comprises of the following cutting edge industry-aligned curriculum with the right blend of statistics, technical and business knowledge:

Course Curriculum: Associate Analytics (Q2101)

Introduction to Analytics and R programming (NOS 2101)

  • Introduction to R, R-Studio (GUI):
  • R Windows Environment,
  • introduction to various data types, Numeric, Character, date, data frame, array, matrix etc.,
  • Reading Datasets,
  • Working with different file types .txt,.csv etc.
  • Outliers
  • Combining Datasets
  • R Functions and loops
  • Summary Statistics - Summarizing data with R
  • Probability
  • Expected, Random,
  • Bivariate Random variables,
  • Probability distribution. Central Limit Theorem etc.

SQL using R & Correlation and Regression Analysis (NOS 2101)

  • Introduction to NoSQL
  • Connecting R to NoSQL databases
  • Excel and R integration with R connector
  • Regression Analysis
  • Assumptions of OLS Regression
  • Regression Modelling
  • Correlation, ANOVA, Forecasting, Heteroscedasticity, Autocorrelation
  • Introduction to Multiple Regression etc.

Understand the Verticals - Engineering, Financial and others (NOS 2101)

  • Understanding systems viz. Engineering Design, Manufacturing, Smart Utilities, Production lines, Automotive, Technology etc.
  • Understanding Business problems related to various businesses

Manage your work to meet requirements (NOS 9001)

  • Understanding Learning objectives
  • Introduction to work & meeting requirements
  • Time Management
  • Work management & prioritization
  • Quality & Standards Adherence

Work effectively with Colleagues (NOS 9002)

  • Introduction to work effectively,
  • Team Work, Professionalism,
  • Effective Communication skills, etc.

Data Management & Introduction to Big Data Tools (NOS 2101)

  • Design Data Architecture and manage the data for analysis
  • Understand various sources of Data like Sensors/signal/GPS etc.
  • Export all the data onto Cloud ex. AWS/Rackspace etc.
  • Introduction to Big Data tools like Hadoop, Spark, Impala etc.
  • Data ETL process, Identify gaps in the data and follow-up for decision making.

Big Data Analytics & Machine Learning Algorithms (NOS 2101)

  • Run descriptive to understand the nature of the available data, collate all the data sources to suffice business requirement
  • Run descriptive statistics for all the variables and observe the data ranges, Outlier detection and elimination.
  • Hypothesis testing and determining the multiple analytical methodologies
  • Train Model on 2/3 sample data using various Statistical/Machine learning algorithms
  • Test model on 1/3 sample for prediction etc.

Data Visualization (NOS 2101)

  • Prepare the data for Visualization
  • Use tools like Tableau
  • QlickView and D3
  • Draw insights out of Visualization tool.

Maintain Healthy, Safe & Secure Working Environment (NOS 9003)

  • Introduction, workplace safety
  • Report Accidents & Emergencies
  • Protect health & safety as your work
  • course conclusion, assessment

Provide Data/Information in Standard Formats (NOS 9004)

  • Introduction, Knowledge Management
  • Standardized reporting & compliances
  • Decision Models
  • Course Conclusion
  • Assessment

Predictive Analytics & Linear, Logistic Regression

  • Python, JAVA, Weka, MS-Excel, SQL
  • Obtain and structure data using standard templates and tools
  • Carry out rule-based analysis of the data in line with the analysis plan
  • Draw justifiable inferences from data analysis

Big Data Analytics

  • Hadoop, HIVE, PIG, Scoop , Spark, Impala

Introduction to Predictive Analytics & Linear Regression (NOS 2101)

  • What and Why Analytics
  • Introduction to Tools and Environment
  • Application of Modelling in Business
  • Databases & Types of data and variables
  • Data Modelling Techniques
  • Missing imputations etc.
  • Need for Business Modelling
  • Regression – Concepts
  • Blue property-assumptions-Least Square Estimation
  • Variable Rationalization and Model Building etc.

Logistic Regression Objective Segmentation (NOS 2101)

  • Model Theory
  • Model fit Statistics
  • Model Conclusion
  • Analytics applications to various Business Domains etc.
  • Regression Vs Segmentation – Supervised and Unsupervised Learning
  • Tree Building – Regression, Classification, Overfitting, Pruning and complexity, Multiple Decision Trees etc.

Time Series Methods/Forecasting, Feature Extraction (NOS 2101)

  • Arima, Measures of Forecast Accuracy
  • STL approach
  • Extract features from generated model as Height
  • Average, Energy etc. and Analyze for prediction.

Working with Documents (NOS 0703)

  • Standard Operating Procedures for documentation and knowledge sharing
  • Defining purpose and scope documents
  • Understanding structure of documents – case studies, articles, white papers, technical reports, minutes of meeting etc.
  • Style and format, Intellectual Property and Copyright
  • Document preparation tools – Visio, PowerPoint, Word, Excel etc.
  • Version Control, Accessing and updating corporate knowledge base, Peer review and feedback.

Develop Knowledge, Skill and Competences (NOS 9005)

  • Introduction to Knowledge skills & competences
  • Training & Development
  • Learning & Development, Policies and Record keeping, etc.


Personality Development

Interview Preparation

Holistic Edge
  • Curriculum created by industry in collaboration with NASSCOM
  • State-of-the-art infrastructure and fully equipped labs
  • Training delivered by Certified and experienced trainers
  • 100% Instructor Led Classroom Training
  • NASSCOM SSC official study material
  • Assessment & Certification from NASSCOM IT-ITES SSC
  • Student loan available from leading financial institutions
  • Globally recognised Certificate
  • Placement assistance
  • Week-end batches for working professional
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