DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN RANCHI

Live Virtual

Instructor Led Live Online

110,000
63,945

  • 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
36,645

  • 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
69,195

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

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA ANALYTICS ONLINE CLASSES IN RANCHI

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 RANCHI

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 : OVERVIEW OF 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
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Biased Random Sampling Methods
  • 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
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Confidence Interval
  • Parametric Hypothesis Testing Methods
  • Hypothesis Testing Errors : Type I And Type Ii
  • One Sample T-test
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test

MODULE 5 : CORRELATION AND REGRESSION

  • Correlation Introduction
  • Direct/Positive Correlation
  • Indirect/Negative Correlation
  • Regression
  • Choosing Right Method
     

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

OFFERED DATA ANALYTICS COURSES IN RANCHI

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN RANCHI

DataMites is one of the top educational institutions in the world because of its strong market position and training of about 50,000 students over the past five years. You should enrol in the Data Analytics Course in Ranchi, which employs a hands-on learning methodology if you are a novice, seasoned professional or manager with a great desire to build a solid foundation in the data-driven industry. 

We provide Data Analytics Course in Ranchi with placement mostly to help people become ready for professions in the field. After finishing their projects and internships, students have more than enough experience to be considered for a job offer that lasts for six months. In Ranchi, the cost of the data analytics course is 42,000 INR. 

Here are the three comprehensive steps that make up our learning process:

Phase 1 is the first step of data analytics training and refers to the period before the training starts. During this time, study aids and other materials are provided and made available for solitary study.

Data analytics online training and capstone projects for upcoming on-the-job training start in phase 2 of the curriculum. Additionally granted is an IABAC Data Analytics Certification!

Projects, internships, and the Job Ready Program for the applicants are just a few of the ways that Phase 3 stands apart and guarantees that the candidates have a complete understanding of the subject matter!

The amount of data produced each day is 2.5 quintillion bytes, and the rate is only rising. It's inevitable that businesses will want to exploit the data they collect as it expands in scope and complexity, and data analysts are leading the charge in this direction. The cost of our certified data analyst course in Ranchi is 55,000 INR, however, right now it's only 44,900 INR. It has IABAC and JainX certifications.

Ranchi is the capital of the Indian state of Jharkhand and is known as the "City of Waterfalls." Ranchi is a charming city full of natural and cultural wonders. Ranchi is a well-known place in Jharkhand that attracts IT firms. Indeed.com reported that a data analyst in Ranchi earns an average amount of 3,11,988 LPA! Get yourself a Data Analytics Training in Ranchi

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

ABOUT DATA ANALYTICS COURSE IN RANCHI

The study of examining unprocessed data to draw inferences about such information is known as data analytics. Many data analytics methods and procedures have been mechanised into mechanical procedures and algorithms that operate on raw data for human consumption.

But make sure you are secure in your profession and talent and confident in it. Moreover, a career in data analytics may be among the most stable and lucrative ones. As a result, we have all the information on the future potential of data analytics, which is extremely relevant in the current environment.

Both business analysts and data analysts contribute to their firms' use of data-driven decision-making. Business analysts typically spend more time addressing business issues and making recommendations, whereas data analysts typically spend more time working directly with the data itself. Both positions are in high demand and are frequently handsomely paid.

Nowadays, firms frequently analyse their data. Choosing the finest data analytics tool might be challenging because no solution can satisfy every need. Among the crucial tools used for data analytics are Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R, and Python.

Anyone who is willing to learn data analytics, whether they are a novice or a seasoned professional, is the simple answer. Engineers, IT workers, software developers, and marketers can all register for the DataMites Data Analytics Course in Ranchi.

A data analytics profession that is pretty robust. Simply put, there has never been a better time to be a data professional. A whopping 2.5 quintillion bytes of data are created every day. The price will vary depending on the degree of instruction you want. Training in data analytics could cost anything from 30,000 to 100,000 Indian rupees.

While a degree isn't necessarily necessary for a data analyst position, getting the necessary certification from a reputable organisation is essential. The skills required for success in data analytics can be learned in anywhere between six weeks and two years. DataMites 4 months of data analytics training can be a great method to master data analytics and become well-versed in it. The vast variation is explained by the fact that there are numerous unique job pathways in data analytics.

Your initial position may be as a junior analyst if you're new to the profession of data analysis. You might be able to land a job as a data analyst if you have some prior experience with transferrable analytical skills.

  • Data Scientist

  • Data Engineer

  • Project Manager

  • Quantitative Analyst

  • Data Analyst Consultant

  • Operations Analyst

  • Marketing Analyst

  • Data Analyst

  • IT Systems Analyst

  • Business Intelligence Analyst

Without intensive training and work, the benefits of a job in data analytics won't materialise. Data analysts need a specific set of abilities in order to succeed in their line of work, and their technical backgrounds are important, but they also need a few soft abilities.

  • Information Display

  • Clearing Data

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

  • Calculus as well as linear algebra

  • Excel for Windows: Communication, Critical Thinking

  • 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 is CHF 95,626 per year in Switzerland. (Glassdoor)

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

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

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

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

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

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

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

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

One of the professions with the highest demand worldwide is skilled data analysis. Data analysts command enormous incomes and top-notch benefits, even at the entry level, because there is such a high demand for their services and a dearth of qualified candidates.  Indeed.com reported that a data analyst in Ranchi earns an average amount of 3,11,988 LPA!

The ideal institute for you, if you want to pursue a career in analytics, is DataMites. The primary mentors are knowledgeable professionals who are industry-oriented, and the course curriculum is well-planned. We provide projects and internship possibilities for the practical experience! The finest educational setting for you, if you want to work in the analytics sector, is DataMites. The primary mentors are knowledgeable and dedicated to the profession, and the course material is well-developed. Projects and internship possibilities are available for professional skills!

The Certified Data Analyst Course, which validates your ability to confidently evaluate data using a variety of technologies, is the highest accreditation in data analytics. The ability to handle data, perform exploratory research, understand the fundamentals of analytics, and visualise, present, and elaborate on your results are all skills that are demonstrated by certification. The respected Jain University and IABAC also accept the DataMites Certified Data Analyst Course in Ranchi.

The comprehensive planning and organisation of the DataMites Data Analytics Training takes into account the fact that beginners to the area are given a thorough explanation of the entire topic. Having said that, if mastering analytics appeals to you, you can sign up without a second thought.

Your greatest option in the field is the DataMites certified data analyst course in Ranchi. Our data analytics course provides you with tangible proof that you are qualified to help companies, including well-known multinationals, interpret the data at hand. It is evidence that you are qualified to carry out the responsibilities of a particular employment role in accordance with industry standards, as opposed to a data analytics certificate.

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FAQ’S OF DATA ANALYTICS TRAINING IN RANCHI

Data analytics classroom training in Ranchi helps to teach useful skills and knowledge and provides valid scope for greater and fluent understanding of the subject matter with a stronger emphasis placed upon cohesiveness, teamwork, and social interaction.

Both seniors and rookies are welcome to enrol in the course. To transition from an IT to a business profile, being a data analyst is the ideal professional move for you to do. If you have strong coding and IT skills, you'll be in a good position to flourish in this industry. Individuals in the human resources, banking, marketing, and sales industries, as well as those who work outside of information technology, are welcome to enrol in DataMites Training.

  • The International Association of Business Analytics Certifications has granted DataMitesTM its accreditation as a global institute for data science (IABAC).

  • roughly 50,000 candidates were trained

  • The three-phase learning process was painstakingly created to deliver the greatest instruction possible.

  • Participate in practical projects and really useful case studies.

  • Obtain the worldwide IABAC and JainX Data Analytics Certification.

  • Help with internships and employment

The cost of Data Analytics Training in Ranchi at DataMites will be around 42,000 INR.

With the proper data analytics training and the required level of experience on your part, a data analyst's potential is virtually limitless. At DataMites, you can take data analytics courses for four months.

The Certified Data Analyst curriculum, one of DataMites' top data analytics programmes, has been recognised by the prestigious organisations IABAC and JainX, whose credentials you would obtain upon successful completion of the programme. To start a data analytics career in Ranchi, it is advisable to earn the DataMites Certified Data Analyst Certification.

DataMites offers a wide range of flexible learning options, such as online data analytics courses in Ranchi, self-study programmes, and classroom training in data analytics. Every training session has been carefully planned to assist participants in becoming authorities in their chosen fields.

Candidates may attend sessions from Datamites for a period of three months pertaining to any query or revision you wish to clear with our Flexi-Pass for Data Analytics Certification Training.

When registering for the certification examinations and receiving your participation certificate, please bring your photo ID proofs, such as a national ID card and driving licence.

Yes, we do offer free demo sessions for prospective students that provide a general idea of what the upcoming course would entail. You are welcome to attend these sessions to receive a sample of what the training will include before deciding whether to continue.

Learning through a case study method ensures that data analytics is taught in the finest and most effective way possible by the greatest instructors in the business.

Yes, you must utilise your data analytics training to the fullest. If you require any additional clarifications, you can without a doubt request help sessions.

Once you've been given the green light by IABAC and Jain University, you'll obtain an IABAC® certification as well as a JainX certification, which will pave the way for your future career in the industry and ensure that your skills are acknowledged globally.

Payments are accepted through;

  • Cash

  • Credit Card

  • PayPal

  • Visa

  • Master Card

  • American Express

  • Net Banking

  • Cheque

  • Debit Card

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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