DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN CHANDIGARH

Live Virtual

Instructor Led Live Online

110,000
62,423

  • IABAC® & JAINx® 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® & JAINx® 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® & JAINx® 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 CHANDIGARH

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 INSTITUTE FOR DATA ANALYTICS COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYTICS CERTIFICATION IN CHANDIGARH

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 objects
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
• Operator’s precedence and associativity

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
• String object basics and inbuilt methods
• List: Object, methods, comprehensions
• Tuple: Object, methods, comprehensions
• Sets: Object, methods, comprehensions
• Dictionary: Object, methods, comprehensions

MODULE 4: PYTHON FUNCTIONS

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

MODULE 5: PYTHON NUMPY PACKAGE

• NumPy Introduction
• Array – Data Structure
• Core Numpy functions
• Matrix Operations

MODULE 6: PYTHON PANDAS PACKAGE

• Pandas functions
• Data Frame and Series – Data Structure
• Data munging with Pandas
• Imputation and outlier analysis

MODULE 1: DATA SCIENCE ESSENTIALS

• Introduction to Data Science
• Data Science Terminologies
• Classifications of Analytics
• Data Science Project workflow

MODULE 2: DATA ENGINEERING FOUNDATION

• Introduction to Data Engineering
• Data engineering importance
• Ecosystems of data engineering tools
• Core concepts of data engineering

MODULE 3: PYTHON FOR DATA ANALYSIS

• Introduction to Python
• Python Data Types, Operators
• Flow Control statements, Functions
• Structured vs Unstructured Data
• Python Numpy package introduction
• Array Data Structures in Numpy
• Array operations and methods
• Python Pandas package introduction
• Data Structures : Series and DataFrame
• Pandas DataFrame key methods

MODULE 4: VISUALIZATION WITH PYTHON

• Visualization Packages (Matplotlib)
• Components Of A Plot, Sub-Plots
• Basic Plots: Line, Bar, Pie, Scatter
• Advanced Python Data Visualizations

MODULE 5: STATISTICS

• Descriptive And Inferential statistics
• Types Of Data, Sampling types
• Measures of Central Tendencies
• Data Variability: Standard Deviation
• Z-Score, Outliers, Normal Distribution
• Central Limit Theorem
• Histogram, Normality Tests
• Skewness & Kurtosis
• Understanding Hypothesis Testing
• P-Value Method, Types Of Errors
• T Distribution, One Sample T-Test
• Independent And Relational T Tests
• Direct And Indirect Correlation
• Regression Theory

MODULE 6: MACHINE LEARNING INTRODUCTION

• Machine Learning Introduction
• ML core concepts
• Unsupervised and Supervised Learning
• Clustering with K-Means
• Regression and Classification Models.
• Regression Algorithm: Linear Regression
• ML Model Evaluation
• Classification Algorithm: Logistic Regression

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Performing Comparison Analysis on Data
• Performing correlation Analysis on Data
• Hands-on case study 1: Comparison Analysis
• Hands-on case study 2 Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Concept of Variability and Variance
• Data Preparation for Variance Analysis
• Business use cases for Variance and Frequency Analysis
• Performing Variance and Frequency Analysis
• Hands-on case study 1: Variance Analysis
• Hands-on case study 2: 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: Procurement Decision with break even

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis
• Insights on Optimizing Operations with Pareto Analysis
• Performing Pareto Analysis on Data
• 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
• Hands-on Case Study: Trend Analysis

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
• Presenting the reports
• Hands-on case study: Create Data Analysis Reports

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Visual Perspective
• Benefits of Business Analytics
• Challenges
• Classification of Business Analytics
• Data Sources
• Data Reliability and Validity
• Business Analytics Model

MODULE 2: OPTIMIZATION MODELS

• Prescriptive Analytics with Low Uncertainty
• Mathematical Modeling and Decision Modeling
• Break Even Analysis
• Product Pricing with Prescriptive Modeling
• Building an Optimization Model
• Case Study 1 : WonderZon Network Optimization
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics beyond Linear Regression
• Hands on: Regression Modeling in Excel
• Case Study 2 : Sales Promotion Decision with Regression Analysis
• Assignment 2 : Design Marketing Decision board for QuikMark Inc.

MODULE 4: DECISION MODELING

• Prescriptive Analytics with High Uncertainty
• Comparing Decisions in Uncertain Settings
• Decision Trees for Decision Modeling
• Case Study 3 : Decision modeling of Internet Plans, Monte Carlo Simulation
• Case Study 4 : Kickathlon Sports Retailer Supplier Decision Modeling

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
• How it works: Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN
• How It Works: Nearest Neighbor Concept
• Hands-on KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• K Means Algorithm
• How it works : K Means theory
• Hands-on K Means Clustering with ML Tool

MODULE 6: ML ALGO: DECISION TREE

• Random Forest Ensemble technique
• How it works: Bagging Theory
• 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
• Modeling and Evaluation of SVM in Python

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN
• How It Works: Back prop, Gradient Descent
• Modeling and Evaluation of ANN in Python

MODULE 9: PROJECT: PREDICTIVE ANALYTICS WITH ML

• Project Business requirements
• Data Modeling
• Building Predictive Model with ML Tool
• Evaluation and Deployment
• Project Documentation and Report

MODULE 1: GIT INTRODUCTION

• Purpose of Version Control
• Popular Version control tools
• Git Distribution Version Control
• Terminologies
• Git Workflow
• Git Architecture

MODULE 2: GIT REPOSITORY and GitHub

• Git Repo Introduction
• Create New Repo with Init command
• Copying existing repo
• Git user and remote node
• Git Status and rebase
• Review Repo History
• GitHub Cloud Remote Repo

MODULE 3: COMMITS, PULL, FETCH AND PUSH

• Code commits
• Pull, Fetch and conflicts resolution
• Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING

• Organize code with branches
• Checkout branch
• Merge branches

MODULE 5: UNDOING CHANGES

• Editing Commits
• Commit command Amend flag
• Git reset and revert

MODULE 6: GIT WITH GITHUB AND BITBUCKET

• Creating GitHub Account
• Local and Remote Repo
• Collaborating with other developers
• Bitbucket Git account

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
• Comments
• import and export dataset

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
• Cross join
• Self join

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
• Hands-on Map Reduce task

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
• Working with Spark SQL Query Language

MODULE 5: MACHINE LEARNING WITH SPARK ML

• Introduction to MLlib Various ML algorithms supported by Mlib
• ML model with Spark ML.
• Linear regression
• logistic regression
• Random forest

MODULE 6: KAFKA and Spark

• Kafka architecture
• Kafka workflow
• Configuring Kafka cluster
• Operations

MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION

• What Is Business Intelligence (BI)?
• What Bi Is The Core Of Business Decisions?
• BI Evolution
• Business Intelligence Vs Business Analytics
• Data Driven Decisions With Bi Tools
• The Crisp-Dm Methodology

MODULE 2: BI WITH TABLEAU: INTRODUCTION

• The Tableau Interface
• Tableau Workbook, Sheets And Dashboards
• Filter Shelf, Rows And Columns
• Dimensions And Measures
• Distributing And Publishing

MODULE 3: TABLEAU: CONNECTING TO DATA SOURCE

• Connecting To Data File , Database Servers
• Managing Fields
• Managing Extracts
• Saving And Publishing Data Sources
• Data Prep With Text And Excel Files
• Join Types With Union
• Cross-Database Joins
• Data Blending
• Connecting To Pdfs

MODULE 4: TABLEAU : BUSINESS INSIGHTS

• Getting Started With Visual Analytics
• Drill Down And Hierarchies
• Sorting & Grouping
• Creating And Working Sets
• Using The Filter Shelf
• Interactive Filters
• Parameters
• The Formatting Pane
• Trend Lines & Reference Lines
• Forecasting
• Clustering

MODULE 5: DASHBOARDS, STORIES AND PAGES

• Dashboards And Stories Introduction
• Building A Dashboard
• Dashboard Objects
• Dashboard Formatting
• Dashboard Interactivity Using Actions
• Story Points
• Animation With Pages

MODULE 6: BI WITH POWER-BI

• Power BI basics
• Basics Visualizations
• Business Insights with Power BI

MODULE 1: ARTIFICIAL INTELLIGENCE OVERVIEW

• Evolution Of Human Intelligence
• What Is Artificial Intelligence?
• History Of Artificial Intelligence.
• Why Artificial Intelligence Now?
• Ai Terminologies
• Areas Of Artificial Intelligence
• Ai Vs Data Science Vs Machine Learning

MODULE 2: DEEP LEARNING INTRODUCTION

• Deep Neural Network
• Machine Learning vs Deep Learning
• Feature Learning in Deep Networks
• Applications of Deep Learning Networks

MODULE 3: TENSORFLOW FOUNDATION

• TensorFlow Installation and setup
• TensorFlow Structure and Modules
• Hands-On: ML modeling with TensorFlow

MODULE 4: COMPUTER VISION INTRODUCTION

• Image Basics
• Convolution Neural Network (CNN)
• Image Classification with CNN
• Hands-On: Cat vs Dogs Classification with CNN Network

MODULE 5: NATURAL LANGUAGE PROCESSING (NLP)

• NLP Introduction
• Bag of Words Models
• Word Embedding
• Language Modeling
• Hands-On: BERT Algorithm

MODULE 6: AI ETHICAL ISSUES AND CONCERNS

• Issues And Concerns Around Ai
• Ai And Ethical Concerns
• Ai And Bias
• Ai: Ethics, Bias, And Trust

OFFERED DATA ANALYTICS COURSES IN CHANDIGARH

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN CHANDIGARH

DataMites™ is the top training provider for data analytics courses in Chandigarh and has a systematically planned curriculum that showcases all-around instruction. DataMites provides a broad range of flexible learning options, together with live online classes, superbly recorded sessions, and hands-on training. Our data analytics certification programme in Chandigarh has been granted recognition from the European Union framework IABAC. You can access a first-rate teaching atmosphere at a fair price via DataMites.

The timeframe of the DataMites Data Analytics Training in Chandigarh is 4 months, and they are available in both online data analytics training in Chandigarh and data analytics classroom course formats. They are delivered using a three-phase teaching methodology.

Phase 1: Candidates will receive leading self-study videos and materials to aid them in completing the complete curriculum as they prepare ready for the following course.

Phase 2 is the primary Live Intensive Training phase, and it contains the IABAC Data Analytics Certification, a global certification, as well as practical capstone projects.

Projects, internships, and a programme to prepare participants for employment comprise Phase 3.

The rising relevance of analytics and data science in India is due to the newfound value of data. As a result, a reputable data analytics certification course in Chandigarh may help you advance your career and gain a head start in the field. With certifications from IABAC & JainX, our Certified Data Analyst Course Fee in Chandigarh is 55,000 INR; however, thanks to a 20% discount, the Certified Data Analyst Training Fee in Chandigarh is now only 44,900 INR. 

Data Analytics technologies and techniques are broadly used in various commercial industries to enable organizations to make business decisions. 

As per the World Economic Forum (WEF) by 2022, 85% of companies will have adopted big data and analytics technologies. WEF also found that 96% of companies were definitely planning or are likely to hire new permanent staff with relevant skills to fill future big data analytics-related roles.

The presence of leading IT businesses in Chandigarh, such as Infosys and Tech Mahindra, has elevated the city to the second largest technological centre in North India, trailing only the National Capital Region (Northern Capital Region comprising New Delhi, Noida and Gurgaon). Chandigarh has become home to a number of other internationally renowned IT firms that are regarded as ideal places to work by IT experts.

Taking up data analytics training in Chandigarh should easily lead to an entry-level data analytics career, especially if you have a good grade point average and a high-class ranking. Despite the fact that the position is entry-level, the salary is higher than that of experienced experts in most industries. As per Payscale, a data analyst's average salary in Chandigarh is 4,19,314 and glassdoor shows that a data analyst in Chandigarh earns an average amount of 5,32,876 LPA! 

Moreover, LinkedIn and the US Bureau of Labor had confirmed that the role of Data Analyst would be the most in-demand by 2022. So why are you still waiting? Take up the Data Analytics Training in Chandigarh. Grab the opportunity!

Along with the data analytics courses, DataMites also provides data science, data engineer, artificial intelligence, deep learning, tableau, machine learning, r programming, and python training courses in Chandigarh.

ABOUT DATA ANALYTICS COURSE IN CHANDIGARH

Data analytics is the process of extracting insights from data that has been extracted, converted, and centralised to find and analyse hidden patterns, relationships, trends, correlations, and anomalies, as well as to verify a theory or hypothesis.

Data analytics is the process of analysing datasets to find trends and insights that are then utilised to guide organisational choices. Business analytics is concerned with analysing different forms of data to produce useful, data-driven business choices and enacting changes in response to those decisions.

If you wish to learn more about the subjects of data analytics and data science, everyone is invited to enrol in the course. The minimum criterion for admission to a postgraduate Data Analytics study is a bachelor's degree with at least 50% overall or the equivalent, preferably in science or computer science from a recognised university.

Yes, but not always. Python, Excel, and SQL knowledge are always preferred. But by starting with the basics, you can surely improve yourself.

The field of data analytics is tremendously rewarding. Simply put, there has never been a more favourable time to work in the data industry. Every day, 2.5 quintillion bytes of data are produced, and this rate is only increasing. Depending on the degree of instruction you want, the cost will change. The Data Analytics training fee in Chandigarh is between 30,000 and 100,000 Indian rupees.

A degree is typically not required for a position as a data analyst, but getting the right certification from an accredited college is crucial. It could take anywhere from six weeks to two years to learn the skills needed for success in data analytics. DataMites 4-month data analytics training programme is an efficient way to learn about and master data analytics. Because there are so many different paths one might take to become a data analytics specialist, the variability is explained by this.

 

A junior analyst position can be available as your first employment if you're new to the field of data analysis. You may be able to land a job as a data analyst if you have some previous experience with transferable analytical skills.

  • Data Analyst Consultant

  • Business Intelligence Analyst

  • Data Analyst

  • Marketing Analyst

  • Data Scientist

  • Data Engineer

  • Project Manager

  • Quantitative Analyst

  • Operations Analyst

  • IT Systems Analyst

Without intensive training and work, a job in data analytics won't yield rewarding results. Data analysts need a special set of abilities to succeed in their line of work, and their education is mostly technological; nevertheless, they also need a few soft skills.

  • Visualization of data

  • Cleaning of Data

  • Machine Learning with MATLAB, R, Python, SQL, and NoSQL

  • Algebra and Calculus

  • Excel for Microsoft, Critical Thinking, Communication

  • The national average salary for a Data Analyst in India is INR 6,00,000 per year. (Glassdoor)

  • The national average salary for a Data Analyst is USD 69,517 per year in the United States. (Glassdoor)

  • The national average salary for a Data Analyst in the UK is £36,535 per annum.  (Glassdoor)

  • The national average salary for a Data Analyst in Australia is AUD 85,000 per year. (Glassdoor)

  • The national average salary for a Data Analyst in Germany is 46,328 EUR per annum. (Payscale)

  • The national average salary for a Data Analyst in UAE is AED 106,940 per year. (Payscale)

  • The national average salary for a Data Analyst in Canada is C$58,843 per year. (Payscale)

  • The national average salary for a Data Analyst in Saudi Arabia is SAR 95,960 per year. (Payscale.com)

  • The national average salary for a Data Analyst in Switzerland is CHF 95,626 per year. (Glassdoor)

  • The national average salary for a Data Analyst in South Africa is ZAR 286,090 per year. (Payscale.com)

The wage rise that goes along with a data analytics career is one profitable part of it. In line with the demand for qualified data analysis specialists, big data job salaries are rising. According to Glassdoor, a data analyst's average salary in Chandigarh is 5,32,876 and indeed revealed that a data analyst in Chandigarh earns a moderate amount of 39,789 per month!

Since there is a growing need for data specialists but a limited supply, there are many excellent work prospects in this industry. If you want to pursue a career in the analytics industry, DataMites is the finest institute for you. The primary mentors are knowledgeable and industry-oriented, and the course curriculum is skillfully laid out. With projects and internship opportunities, we provide practical training!

Data analytics is a concept that has gained popularity in recent years due to the growth in data generation. Although there are no formal prerequisites for the DataMites Data Analytics Course because it is designed to train candidates starting at level 1, having prior knowledge of programming languages, databases, data structures, mathematics, and algorithms only serves to be desirable.

The ultimate accreditation in data analytics is the Certified Data Analyst designation, which attests to your competence in confidently evaluating data utilising a range of technologies. Your proficiency in manipulating data, conducting exploratory research, comprehending the fundamentals of analytics, and visualising, presenting, and expanding on your findings is demonstrated by your certification. The DataMites Certified Data Analyst Course in Chandigarh is recognised by both IABAC and the prestigious Jain University.

Your highest bet in the field is the DataMites data analyst certification course in Chandigarh. Our data analytics training provides you with tangible proof that you are qualified to help businesses, including well-known multinationals, interpret the data at hand. It is evidence that you are qualified to carry out the responsibilities of a certain job role in accordance with industry standards, as opposed to a data analytics certificate.

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FAQ’S OF DATA ANALYTICS TRAINING IN CHANDIGARH

You may grow in your career and apply for the highest-paying opportunities with data analytics training that is specific to the needs of the sector. Having the ability to work with data is no longer optional given the surge in the use of analytics. The importance of data analytics skills will only increase as more sectors and businesses come on board.

The International Association of Business Analytics Certifications has approved DataMitesTM, a global institute for data science (IABAC).

  • Trained more than 50,000 candidates

  • To provide the finest instruction possible, the three-phase learning technique was meticulously planned.

  • Participate in worthwhile case studies and real-world projects.

  • Obtain the global IABAC and JainX Data Analytics Certification.

  • Assistance with internships and employment

Data analytics classroom training in Chandigarh helps to teach useful skills and knowledge and allows valid opportunities for a deeper and fluent understanding of the subject matter since a greater emphasis is placed on collaboration, cooperative learning, and social interaction. Our online data analytics courses in Chandigarh are just as effective.

Both undergraduates and freshmen may enrol in the course. The best job choice for you will be pursuing a profession as a data analyst if you want to go from an IT profile to a business profile. Your chances of succeeding in this sector are strong if you have any talent for coding and IT skills. DataMites Data Analytics Certification Training is open to non-IT individuals working in industries including sales, marketing, banking, and human resources.

Training in data analytics at DataMites in Chandigarh will cost about 42,000 INR.

We want to develop knowledgeable people in the domain because data analytics has grown to be a large field. Our instructors at DataMites are highly knowledgeable and have hands-on experience in the data field, so they can provide the finest learning environment for your upcoming major step.

You should absolutely finish the DataMites Certified Data Analyst Training if you're thinking about a profession in data analysis. Our curriculum promises to offer the knowledge, assurance, and qualifications necessary to start a data analysis career from zero.

One of the top data analytics programmes offered by DataMites is the Certified Data Analyst curriculum, which has been accredited by the IABAC and JainX extremely prominent agencies, whose credentials you would receive after completing the course. The best way to begin a career in data analytics is to obtain the DataMites Certified Data Analyst certification.

Once you have been validated by IABAC and Jain University, you will obtain an IABAC® certification and a JainX certification, opening the door for your future job in the industry and ensuring that your skills are recognised globally.

For a duration of three months, candidates may follow Datamites sessions related to any question or revision they wish to clearing with our Flexi-Pass for Data Analytics Certification Training in Chandigarh.

The DataMites Data Analytics Training is skillfully planned and structured to ensure that novices to the area are given a thorough explanation of the entire domain. That being said, if understanding analytics piques your interest, you can sign up without a second thought.

A three-phase learning process is offered by DataMites. Candidates will be given books and self-study DVDs to use throughout Phase 1 to assist them learn everything there is to know about the programme. The main part of the intensive live online training is Phase 2, and it culminates in the awarding of the IABAC Data Analytics Certification, a universal credential. Additionally, we will assign tasks and placements during the third phase.

Yes, DataMites has a specialised Placement Assistance Team (PAT) that will offer you job placement services, interview preparation, and other services after the course is over.

Yes, in fact, we do provide free demo sessions for prospective students that provide a general idea of what the forthcoming course would entail. You are welcome to attend these sessions in order to acquire a feel for the training and make a decision regarding whether to continue or not.

Bring your photo identification with you when you register for the certification exams and when we issue you a participation certificate, such as a national ID card and a driver's licence.

We accept payments using;

  • Cash

  • Credit Card

  • PayPal

  • American Express

  • Debit Card

  • Visa

  • Master Card

  • Net Banking

  • Cheque

Using your particular certification number, you can verify all certificates at DataMites®.com. A different option is to email care@DataMites®.com.

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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