DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS COURSE LEAD MENTORS

DATA ANALYTICS COURSE FEE IN PERUNGUDI, CHENNAI

Live Virtual

Instructor Led Live Online

110,000
62,423

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

55,000
35,773

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Classroom

In - Person Classroom Training

110,000
67,548

  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship +Job Assistance

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UPCOMING DATA ANALYTICS ONLINE CLASSES IN PERUNGUDI

BEST DATA ANALYTICS CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES FOR DATA ANALYTICS TRAINING

Why DataMites Infographic

SYLLABUS OF DATA ANALYTICS CERTIFICATION COURSE

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain

MODULE 2: CLASSIFICATION OF ANALYTICS

• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics

MODULE 3: CRIP-DM Model

• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
Modeling, Evaluation, Deploying,Monitoring

MODULE 4: UNIVARIATE DATA ANALYSIS

• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.

MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS

• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot

MODULE 6: BI-VARIATE DATA ANALYSIS

• Scatter Plots
• Regression Analysis
• Correlation Coefficients

MODULE 1: PYTHON BASICS

• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

MODULE 2: PYTHON CONTROL STATEMENTS

• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES

• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

  • Introduction to Statistics
  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's Minimum Sample Size
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of Hypothesis testing

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis

MODULE 3: RANKING ANALYSIS

• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis

MODULE 4: BREAK EVEN ANALYSIS

• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis

MODULE 6: Time Series and Trend Analysis

• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

MODULE 1: MACHINE LEARNING INTRODUCTION

• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised

MODULE 2: ML ALGO: LINEAR REGRESSSION

• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool

MODULE 3: ML ALGO: LOGISTIC REGRESSION

• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool

MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

MODULE 1: DATABASE INTRODUCTION

• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)

MODULE 2: SQL BASICS

• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS

• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL)

• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table

MODULE 5: SQL JOINS

• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank

MODULE 6: SQL COMMANDS AND CLAUSES

• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries

MODULE 7: DOCUMENT DB/NO-SQL DB

• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management

MODULE 1: BIG DATA INTRODUCTION

• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction

MODULE 2: HDFS AND MAP REDUCE

• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION

• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE

• Introducing Spark SQL
• Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS

• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies

MODULE 2: POWER-BI BASICS

• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION

MODULE 3: DATA TRANSFORMATION TECHNIQUES

• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES

• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model

OFFERED DATA ANALYTICS COURSES IN PERUNGUDI

DATA ANALYTICS TRAINING COURSE REVIEWS

ABOUT DATA ANALYTICS COURSE IN PERUNGUDI

The Data Analytics course in Perungudi provides theoretical insights with hands-on practice to enhance students' analytical skills to thrive in the data-driven industry. According to Acumen Research and Consulting, the size of the Global Data Analytics Market reached USD 31.8 Billion in 2021 and is anticipated to expand to USD 329.8 Billion by 2030, with a compound annual growth rate (CAGR) of 29.9% from 2022 to 2030. Additionally, the data analyst's salary in Perungudi ranges from INR 6,72,866 per year according to a Glassdoor report.

DataMites, a globally recognized institute, provides specialized Data Analytics Courses in Perungudi, focusing on professional development in cutting-edge technologies like data science, data engineering, artificial intelligence, machine learning, and Python. With international accreditation from IABAC, students completing the courses receive globally recognized certifications. Having a decade of experience, DataMites has successfully trained over 50,000+ learners worldwide. The Data Analytics training in Perungudi, led by seasoned mentors, equips students to make well-informed decisions about their career paths.

DataMites presents a Certified Data Analyst Training Course in Perungudi spanning Six months. This program delves into crucial subjects, including MySQL, Power BI, Excel, and Tableau, offering an extensive learning experience of 200 hours. Additionally, DataMites extends offline training in data analytics at the Perungudi location, ensuring students acquire foundational insights into the field. The institute further supports students by facilitating internship and job programs, enhancing their career prospects.

DataMites provides in-depth Data Analytics Training in Perungudi, encompassing:

  1. Distinguished Faculty Headed by Ashok Veda
  2. Comprehensive and Organized Curriculum
  3. Supply of Physical Learning Resources and Books
  4. Competitive and Cost-Effective Pricing with Scholarship Options
  5. Support for Resume Building
  6. Involvement in Real-world Client Projects
  7. Membership in the Exclusive DataMites Learning Community
  8. Global IABAC Certification upon Successful Completion
  9. Versatile Training Formats: Online, Offline, and Blended, with Practical Projects
  10. Round-the-clock job and Placement Support
  11. Focused Live Online Training

Perungudi, a bustling suburb in Perungudi, seamlessly blends residential tranquillity with emerging commercial developments, making it a dynamic and sought-after locale The demand for data analytics in Perungudi is rapidly growing as organizations seek to harness the power of data to gain strategic insights and improve decision-making. Data analytics professionals play a pivotal role in interpreting complex data sets, driving innovation, and enhancing overall business performance. To access comprehensive details about the course, join DataMites and enjoy the exclusive benefits of our training programs.

ABOUT DATAMITES DATA ANALYTICS COURSE IN PERUNGUDI

Data analytics is the process of using statistical and computational methods to extract valuable insights from data.

Data analytics is employed by various industries, including marketing, finance, healthcare, and government, to make informed decisions based on data.

Data analytics offers substantial career growth potential, with a projected job growth of 15% between 2020 and 2030 and an average annual salary of $98,230 in 2020.

Key skills include proficiency in programming languages like Python and R, statistical analysis, data visualization, and machine learning.

Job roles include data analyst, data scientist, business analyst, and data engineer.

Popular tools include Tableau, Excel, SQL, and programming libraries like Pandas and Scikit-learn in Python.

Requirements vary by institution but generally favour a background in mathematics or computer science.

The course fee typically ranges from 50,000 to 80,000.

The data analyst's salary in Perungudi ranges from INR 6,72,866 per year according to a Glassdoor report.

The role involves analyzing data to extract insights and trends, aiding individuals and organizations in making well-informed decisions.

Yes, data analytics offers numerous opportunities with the potential for high salaries, especially for experienced professionals.

Yes, there is a high demand for data analysts as businesses increasingly rely on data-driven decision-making.

Yes, recent graduates with relevant degrees and analytical skills can start their careers as entry-level data analysts.

While not inherently difficult, it requires specific technical skills and ongoing education due to continuous advancements in the field.

Working in data analytics can be demanding with long hours and strict deadlines, emphasizing the importance of maintaining a healthy work-life balance.

Essential skills encompass proficiency in programming languages like Python and R, statistical analysis, data visualization, and machine learning.

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FAQ'S OF DATA ANALYTICS TRAINING IN PERUNGUDI

DataMites Institute stands out for data analytics due to its experienced trainers, comprehensive curriculum, and hands-on training approach. Their practical-oriented training, real-world projects, and placement assistance make them a preferred choice for learners looking to enhance their data analytics skills.

Enrolling in a data analytics course at DataMites offers benefits such as practical hands-on training, expert instructors, a well-rounded curriculum, industry-recognized certifications, and flexible learning options. Additionally, they provide career support.

The data analytics course at DataMites in Perungudi has a flexible duration of six months, with 200+ learning hours. Students are expected to dedicate 20 hours per week, and they have one-year access to e-learning resources.

The course fee for the data analytics course at DataMites in Perungudi ranges from INR 35,773 to INR 110,000.

Flexi-Pass at DataMites is a learning option allowing students to access course content for a specific period, enabling them to complete the course at their own pace. It includes pre-recorded video lectures, study materials, and online assessments, providing flexibility for students with other commitments.

Yes, DataMites offers a free demo class to interested students, providing an opportunity to experience the teaching style, course content, and overall learning environment before enrolling.

Yes, upon completing the data analytics courses in Perungudi at DataMites, students receive industry-recognized certifications, enhancing their career prospects.

DataMites accepts various payment methods for online courses, including cash, net banking, checks, debit cards, credit cards, PayPal, Visa, Mastercard, and American Express.

The premier data analytics course at DataMites is the Certified Data Analytics Course in Perungudi.

The Certified Data Analytics (CDA) course at DataMites is open to individuals new to data analytics, requiring no prior coding knowledge or experience, making it accessible to anyone interested in gaining valuable skills in the field.

Embarking on a data analytics course in Perungudi at DataMites offers several advantages, including a comprehensive curriculum, industry-relevant training, experienced trainers, hands-on learning, certification, and placement support.

Students with a fundamental grasp of analytics and a background in mathematics are encouraged to consider enrolling in the data analytics course at Perungudi.

DataMites is committed to delivering instructors who hold certifications, possess extensive industry experience spanning decades, and demonstrate a profound understanding of the subject matter.

DataMites provides candidates with versatile learning options, offering both online data analyst training and engaging classroom sessions in data analytics, allowing students to choose the mode that suits them best.

The Certified Data Analyst curriculum at DataMites is recognized by authorities such as IABAC and NASSCOM. Completing the course leads to credentials endorsed by these reputable organizations, providing an excellent pathway to initiate a career in the field of data analytics.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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