DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN KANPUR

Live Virtual

Instructor Led Live Online

110,000
63,945

  • 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
36,645

  • 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
69,195

  • 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 KANPUR

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 KANPUR

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 KANPUR

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN KANPUR

DataMitesTM, a global institute for data analytics programmes, features a carefully thought-out curriculum that shows all-around training. DataMites offers a variety of flexible learning opportunities, including online data analytics courses in Kanpur, superbly recorded sessions, and hands-on training. Our data analytics certification programme in Kanpur has received accreditation from IABAC, a foundation for the European Union. Use DataMites to get a top-notch learning environment at a fair fee.

Being trained in data analytics and accredited as a data analytics professional has several advantages in the era of big data. If you want to become a data scientist, engineer, or analyst, you might want to think about getting the DataMites data analytics training in Kanpur. With our aid of industry-designed Data Analytics Certification Courses in Kanpur, you may progress your career and apply for the highest-paying positions. Candidates are taught everything from scratch because the course is comprehensive in and of itself. The data analytics course fee in Kanpur is 42,000 INR. 

Data is today's holy grail, and with the best data analytics training - Certified Data Analyst Course in Kanpur, you may ascend to the rank of high priest within the data analytics community. The Certified Data Analyst Programme will help you develop an analytical mindset, help you understand the fundamental competencies that power the business, and help you overcome these obstacles. Our Certified Data Analyst Course Fee in Kanpur is 55,000 INR, but it's currently available for 44,900 INR instead. It has certifications from IABAC & JainX.

The DataMites Data Analytics Certification Courses in Kanpur are offered over a period of four months and include both classroom and online components that follow a three-phase teaching methodology. 

Phase 1 is the initial level, and it comprises providing students with the necessary study materials as well as access to videos and other resources for independent study.

Phase 2 = Offers an interactive capstone project, the IABAC Data Analytics Credential, and online training for data analytics.

The 3rd phase of the programme includes projects, internships, and the Job Ready Program.

Data Analytics has become crucial as it aids in upgrading business, improving decision making and providing the biggest edge over the competitors. Because a data analyst's job is different from other corporate jobs in this way. The status of a data analyst is therefore comparable to that of a celebrity. Data analytics jobs are profuse, incomes are good, and there are several career options to choose from. As a result, with high pay and growth goals. According to glassdoor, a data analyst's average salary in Kanpur is 7,00,126 LPA!

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

Join Data Analytics Training in Kanpur. Grab your chance!

ABOUT DATA ANALYTICS COURSE IN KANPUR

The analysis of raw data to provide meaningful, useful insights is known as data analytics. Smart business decisions are then driven by and informed by these insights. Therefore, a data analyst will gather raw data, arrange it, and then analyse it to turn it from a collection of illogical numbers into a coherent body of knowledge.

The basic answer is everyone eager to learn data analytics, whether they are seasoned professionals or complete beginners. It is possible for engineers, software developers, IT specialists, and marketers to take up the DataMites Data Analytics Course in Kanpur.

  • Data analytics is becoming a top priority for top businesses.

  • There are more positions open.

  • Professional pay for data analytics is increasing.

  • Big data analytics is prevalent everywhere you look.

  • You will be able to select from a range of job titles and play a crucial role in how the business makes decisions.

One of the most in-demand professions for 2022 is data analysis. India is the second major location for data occupations after the United States. Depending on the degree of instruction you want, the cost will change. The cost of the Data Analytics training in Kanpur is between 30,000 and 100,000 Indian rupees.

A degree is not often required for work as a data analyst, but it is crucial to get the right certification from an accredited college. The time it takes to learn the skills needed for success in data analytics might range from six weeks to two years. DataMites 4-month data analytics training programme in Kanpur is a good way to learn about and get expertise in data analytics. The variability is accounted for by the several distinctive paths one could pursue to become a data analytics specialist.

If you're new to the field of data analysis, you may start off as a junior analyst. If you have any previous experience with transferable data analytical skills, you might be able to get work as a data analyst.

  • Business Intelligence Analyst

  • Operations Analyst

  • Marketing Analyst

  • Data Analyst

  • Data Scientist

  • Data Engineer

  • Quantitative Analyst

  • Data Analyst Consultant

  • Project Manager

  • IT Systems Analyst

Both business analysts and data analysts support data-driven decision-making inside their businesses. Business analysts are typically more active in addressing business issues and making recommendations while data analysts typically work more directly with the data itself. Both positions are in high demand and can pay well.

 Learning data analytics would benefit from having technical abilities including data analysis, statistical knowledge, data narrative, communication, and problem-solving. For data analysts who frequently collaborate with business stakeholders, business intuition and strategic thinking are also seen as crucial skills.

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

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

The income rise that comes with a profession in data analytics is one of its rewarding aspects. The pay for big data positions is rising in line with the demand for skilled data analysts. According to glassdoor, a data analyst's salary in Kanpur is 7,00,126 LPA!

Because there is an increasing demand for data specialists and a small supply, those in this industry have strong employment prospects. DataMites is the best educational facility for you if you want to pursue a career in the analytics industry. The data analytics course material is well developed, and the major mentors are skilled and committed to the industry. For real skills, projects and internship opportunities are available!

The top qualification in data analytics is Certified Data Analyst, which verifies your capacity to confidently assess data using a range of technologies. A certification demonstrates your proficiency in manipulating data, conducting exploratory research, comprehending the fundamentals of analytics, and visualising, presenting, and expanding on your results. The DataMites Why should you choose DataMites for Certified Data Analyst Training in Kanpur? has earned recognition from both IABAC and the renowned Jain University.

The DataMites data analyst certification programme in Kanpur is your best choice in this profession. You can obtain strong evidence from our data analytics course that you are qualified to assist businesses, particularly well-known multinationals, in interpreting the data at hand. In contrast to a data analytics certificate, it is proof that you are qualified to perform the duties of a certain work role in line with business needs.

Furthermore, sophisticated coding expertise is not necessary for data analysts. As opposed to that, they ought to have knowledge in data management, analytics, and visualisation software. The majority of data-related occupations require strong mathematics skills, and data analysts are no exception.

The discipline of data analytics is both challenging and lucrative. You would need to be very diligent to succeed in this industry because it is difficult to find employment in the field. A person does not suddenly become a data analyst. If you want to begin a career in data analytics as a novice, DataMites can help you study, gain experience, and comprehend the principles.

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FAQ’S OF DATA ANALYTICS TRAINING IN KANPUR

Both freshmen and undergraduate students may enrol in the course. Following a profession as a data analyst will be the best choice for you if you want to go from an IT profile to a business profile. You will have a decent chance of succeeding in this sector if you have any potential for coding and IT skills. DataMitesTraining is also open to non-IT professionals working in industries like human resources, banking, marketing, and sales, among others.

The International Association of Business Analytics Certifications has approved the global institute for data science known as DataMitesTM (IABAC).

  • trained more than 50,000 applicants

  • To provide the greatest instruction possible, the three-phase learning technique was painstakingly created.

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

  • Obtain the international certifications IABAC and JainX Data Analytics.

  • Job assistance and internships

DataMites charges about 42,000 INR for data analytics training in Kanpur.

In a data-driven workplace, completing data analytics training and becoming a certified data analytics specialist have several benefits. DataMites will train you in data analytics over a period of four months.

The DataMites Certified Data Analyst Training is required if you're thinking about working in data analysis. Our curriculum is certain to provide the education, experience, and qualifications required to begin working as a data analyst right away.

Data analytics has grown to be a large field, so we want to develop skilled workers in the domain. 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 big move.

Our Flexi-Pass for Data Analytics Certification Training allows applicants to attend sessions from Datamites for a period of three months pertaining to any query or revision you wish to clear.

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.

Upon conclusion of the course, you will surely receive a course completion certificate from DataMites.

You don't have a dilemma with that. Speak with your trainers about the matter to arrange a class that meets your schedule. You may simply pick up the content you missed at your own pace and comfort by watching the recordings and uploads of every session of the online data analytics training in Kanpur. The ability to grasp data analytics has never been so straightforward!

For the first time, DataMites' data analytics training online in Kanpur is just as efficient as traditional classroom instruction. The assignment helps students not only learn the material, but also improve their time management skills, which in turn promotes better interaction and more feedback between you and your tutor. Online learning is frequently more cheap than traditional classroom instruction.

Yes, we do provide free demo sessions that give prospective students a general picture of what the upcoming course would entail. You are welcome to attend these sessions to get a feel for the programme and then decide whether to progress with it or not.

Payment can be made via;

  • Cash

  • Credit Card

  • PayPal

  • Visa

  • Master Card

  • American Express

  • Debit Card

  • Net Banking

  • Cheque

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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