DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN DHANBAD

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

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UPCOMING DATA ANALYTICS ONLINE CLASSES IN DHANBAD

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 DHANBAD

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 DHANBAD

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN DHANBAD

DataMitesTM is one of the top providers in India due to its dominant position in the industry and five years of teaching about 50,000 students. Newcomers to data analytics and seasoned professionals with a strong desire to establish a firm foundation in the data-driven sector should enrol in the practical Data Analytics course in Dhanbad. To prepare people for professions in data science, we primarily provide Data Analytics Training in Dhanbad 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 Dhanbad. 

Our learning approach is composed of the three explicit steps listed below:

Data analytics training starts with Phase 1, which is the time before the training actually starts. There are resources and study aids available for solitary study at this time.

Online data analytics training and capstone projects are the first components of phase 2 of the curriculum for upcoming on-the-job training. Also given is an IABAC credential in data analytics!

Projects, internships, and the Job Ready Program for the applicants are a few ways that Phase 3 separates from Phase 2 and guarantees that the candidates have a profound understanding of the subject matter!

Your future job in data will be made possible by our committed career services and the DataMites Certified Data Analyst Course in Dhanbad. By helping you launch your new job in the data sector, DataMites will assist you in earning a professional certification.

A data analyst certification verifies your knowledge and skill in a particular field of big data analysis. Finding a traditionally-trained data analyst who can use the plethora of corporate data analytics tools and processes is nearly impossible, even for major corporations. Although it is presently only 44,900 INR, our certified data analyst course in Dhanbad would typically cost 55,000 INR. There are IABAC and JainX certifications

After Jamshedpur, Dhanbad has the second-highest population density in Jharkhand. Dhanbad is frequently referred to as the "Coal Capital of India" since it is the location of one of the largest coal mines in India. The growth of several IT enterprises is evidence of Dhanbad's IT-boom.

Despite the position being entry-level, the pay is greater than that of experienced professionals in the majority of businesses. The average pay for a data analyst in India is $4,64,926 according to Payscale. In Dhanbad, the average salary for a data analyst is 3,10,279 LPA. (Indeed)

Furthermore, by 2022, the position of Data Analyst would be the most in-demand, according to LinkedIn and the US Bureau of Labor. So what is holding you back? Join DataMites Data Analytics Training in Dhanbad. Embrace the chance!

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 Dhanbad.

ABOUT DATA ANALYTICS COURSE IN DHANBAD

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 Dhanbad.

  • 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 Dhanbad 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 Dhanbad 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.

  • Quantitative Analyst

  • Data Analyst Consultant

  • Project Manager

  • Business Intelligence Analyst

  • Operations Analyst

  • Marketing Analyst

  • Data Analyst

  • Data Scientist

  • Data Engineer

  • 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.

  • 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 ZAR 286,090 per year in South Africa. (Payscale.com)

  • 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)

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 income rise that comes with a profession in data analytics is one of its rewarding aspects. The average pay for a data analyst in India is $4,64,926 according to Payscale. In Dhanbad, the average salary for a data analyst is 3,10,279 LPA. (Indeed)

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 Certified Data Analyst Course in Dhanbad has earned recognition from both IABAC and the renowned Jain University.

The DataMites data analyst certification programme in Dhanbad 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.

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.

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.

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FAQ’S OF DATA ANALYTICS TRAINING IN DHANBAD

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 Dhanbad.

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.

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 Dhanbad. The ability to grasp data analytics has never been so straightforward!

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.

For the first time, DataMites' data analytics training online in Dhanbad 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;

  • Master Card

  • American Express

  • Cash

  • Credit Card

  • PayPal

  • Visa

  • 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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