DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN CUTTACK

Live Virtual

Instructor Led Live Online

110,000
59,378

  • 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
34,028

  • 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
64,253

  • 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 CUTTACK

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 CUTTACK

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 CUTTACK

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN CUTTACK

DataMites has a strong market position and has trained nearly 50,000 students over the past five years, making it one of the best training institutions in the globe. Even if you are a newcomer to data analytics and a seasoned professional with a strong desire to establish a firm foundation in the data-driven sector should enrol in the practical Data Analytics Course in Cuttack. To prepare people for professions in data analytics, we primarily provide Data Analytics Training in Cuttack with placement. Students have more than enough experience after completing their assignments and internships to be evaluated for a job offer within a six-month length. The cost of the data analytics course is 42,000 INR in Cuttack. 

The three thorough steps that make up our learning strategy are as follows:

Phase 1 of data analytics training refers to the time before the training really begins. For solo study during this period, study aids and other materials are offered and made available.

Phase 2 of the programme is when the online training for data analytics and the capstone projects for upcoming on-the-job training begin. An IABAC Data Analytics Certification is additionally awarded!

Phase 3 distinguishes itself and ensures that the candidates have a thorough comprehension of the subject matter through projects, internships, and the Job Ready Program for the applicants, to name just a few things!

Of course, a career in data analytics is lucrative. To put it simply, working with data has never been more exciting. 2.5 quintillion bytes of data are created every day, and the rate is only increasing. As data collection grows in scope and complexity, organisations will inevitably want to use it, and data analysts are leading the way in this direction. Although it is presently only 44,900 INR, our certified data analyst course in Cuttack would typically cost 55,000 INR. There are IABAC and JainX certifications.

Cuttack is a well-known city in eastern Odisha, located near the mouth of the Mahanadi River delta. Cuttack is known as Odisha's Millennium City, Silver City, and Street Food Capital. Data Analytics and Data Science have become a highly profitable industry and to find such a top-rated course that is pretty close to your reach is insane. 

As per Payscale, a data analyst's average salary in India is 4,64,926. A data analyst in Cuttack earns an average amount of 1,93,189 LPA! (Indeed) Gift yourself our certified Data Analytics training in Cuttack!

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 Cuttack.

ABOUT DATA ANALYTICS COURSE IN CUTTACK

Data analytics is the study of examining unprocessed data to draw inferences about that data. Numerous methods and procedures used in data analytics have been mechanised into mechanical procedures and algorithms that operate on raw data for human consumption.

Though each has its own significance, there are some fundamental contrasts between business analytics and data analytics. The activity of examining databases to determine the data they contain is known as "data analytics." Using data analysis tools, you can take raw data and look for patterns to gain insightful knowledge. Business analytics is a practical use of statistical analysis that emphasises giving useful guidance.

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 courses in Cuttack.

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.

As insights helped businesses acquire a competitive advantage, data analysis tools became widely used. Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R, and Python are several of the essential tools used for data analytics.

Data analysis will rule the future. The improvement of data gathering, processing, and interpretation will lead to increased productivity. The world's most in-demand talents today include skilled data analysts. Even at the entry level, Data Analysts earn enormous pay and fantastic benefits due to the high demand for their services and the small pool of qualified candidates.

While obtaining the necessary accreditation from a reputable institution is mandatory, a degree is not usually necessary for a position as a data analyst. The time it takes to acquire the skills required for success in data analytics might range from six weeks to two years. An effective strategy to learn data analytics and become skilled at it is to take a 4-month training course. Data analytics careers can be pursued in a variety of ways, which accounts for the wide spectrum.

Data analytics offers employment prospects and skills outside of the computer and digital industries.

  • Business Intelligence Analyst

  • Data Analyst

  • Quantitative Analyst

  • Data Analyst Consultant

  • Operations Analyst

  • Marketing Analyst

  • Data Scientist

  • Data EngineerProject Manager

  • IT Systems Analyst

The advantages of a position in data analytics won't materialise without extensive training and effort. To be successful in their line of work, data analysts need a specific set of skills, and while having a technical background is vital, they also need a few soft skills.

  • Clearing Data Displaying Information

  • Along with linear algebra, NoSQL Machine Learning Calculus, MATLAB, R, Python, and Python.

  • Excel for Windows, Critical Thinking and Communication

  • 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 INR 6,00,000 per year in India. (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 C$58,843 per year in Canada. (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 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 CHF 95,626 per year in Switzerland. (Glassdoor)

  • 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)

The rise in pay that comes with a profession in data analytics is one of its rewarding aspects. In line with the rise in demand for data analytic skills, big data occupations are paying out more money. As per Payscale, a data analyst's average salary in India is 4,64,926. A data analyst in Cuttack earns an average amount of 1,93,189 LPA! (Indeed)

The majority of the time, a degree is not required for employment as a data analyst, but it is crucial to get the right certification from an accredited institute. It can take anywhere between six weeks and two years to master the skills necessary for success in data analytics. Taking a 4-month training course is an efficient way to learn about and gain expertise in data analytics. The variety is accounted for by the fact that there are a wide range of distinctive paths one can take to become a data analytics professional.

The most valuable certification in data analytics is the Certified Data Analyst Course, which attests to your competence in confidently evaluating data utilising a variety of technologies. Your competence in handling data, doing exploratory research, understanding the fundamentals of analytics, and visualising, presenting, and expanding on your findings are all demonstrated by your certification. IABAC and the esteemed Jain University both acknowledge the DataMites Certified Data Analyst Training in Cuttack.

Through the Certified Data Analyst Course, we provide you with tangible proof that you are qualified to help companies, including well-known multinationals, interpret the data at hand through our data analytics training. It is evidence that, in contrast to a data analytics certificate, you are qualified to carry out the responsibilities of a particular job role in accordance with professional standards.

The DataMites Data Analytics Certification Training in Cuttack is painstakingly planned and organised in this way to ensure that newcomers to the field are given a thorough explanation of the entire subject. If learning analytics interests you, you can sign up right away.

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FAQ’S OF DATA ANALYTICS TRAINING IN CUTTACK

The course is open to both experienced and novices. A career as a data analyst is the most suitable choice for you if you wish to go from an IT to a business profile. If you are proficient in coding and IT, you will be well-suited to flourish in this industry. A person who works in the human resources, banking, marketing, or sales industries, as well as anyone else is 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

At DataMites the Data Analytics Training Fee in Cuttack will be around 42,000 INR

You may develop your career and apply for the highest paid jobs by taking courses in data analytics that have been specifically created for the industry. At DataMites, you would receive 4 months of data analytics training.

When you successfully complete the programme, you will receive certifications from the prominent organisations IABAC and JainX, which have recognised the Certified Data Analyst curriculum as one of DataMites' best data analytics programmes. It is advised to obtain the DataMites Certified Data Analyst certification before beginning a career in data analytics.

On demand, we do provide classroom instruction at your site. Despite the fact that our training allows you to study from anywhere in the world without having to travel or adhere to a strict timetable. There are benefits to studying at your own pace with a curriculum that is equally as useful as for in-class instruction.

At DataMites, there are several flexible learning options available, including live online classes and self-study programmes in data analytics. Each training session is created with the intention of assisting participants in becoming authorities in the subject matter they have picked.

Please bring your photo ID evidence, such as a national ID card and driving licence, when registering for the certification exams and receiving your participation certificate.

Making ensuring that data analytics is taught in the finest and most effective way possible by the greatest instructors in the business is learning through a case study approach.

You must undoubtedly maximise the benefits of your data analytics training. If you require any additional clarifications, you can ask for help sessions without a doubt.

DataMites offers a three-stage learning process. Candidates will be given self-study materials and videos throughout Phase 1 to assist them in learning all there is to know about the programme. You will obtain IABAC Data Analytics Credential, a global certification, after completing Phase 2, the first step of intensive live online training. We will also announce projects and placements during the third phase.

You are not concerned about that. Just talk to your trainers about it to arrange a class that works with your schedule. Each session of the online data analytics training in Cuttack will be videotaped and published, enabling you to easily catch up on the information you missed at your own pace and ease. Understanding data analytics has never been that easy, for sure!

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.

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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