DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN GHAZIABAD

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 GHAZIABAD

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.

images not display images not display

WHY DATAMITES INSTITUTE FOR DATA ANALYTICS COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYTICS CERTIFICATION IN GHAZIABAD

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 GHAZIABAD

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN GHAZIABAD

Because of its solid market position and five years of teaching around 50,000 students, DataMites is one of the top educational institutions around the globe. The Data Analytics Course in Ghaziabad is for those who are new to data science and experienced professionals who have a strong desire to establish a strong foundation in the data-driven sector. We primarily offer data analytics training in Ghaziabad with placement to prepare people for professions in data science. Students who have completed their coursework and internships have gained sufficient work experience to be considered for a position with a six-month tenure. The cost of the data analytics course is 42,000 INR in Ghaziabad.

We take the following three thorough processes in our learning process:

The period before the training begins is referred to as Phase 1 and is the initial stage of data analytics training. Materials and study aids are made available for solitary study during this time.

For upcoming on-the-job training, Phase 2 of the curriculum begins with online data analytics training and capstone projects. Certification in data analytics from IABAC is also awarded!

A few of the ways that Phase 3 differs and ensures that the candidates have a thorough comprehension of the subject matter are projects, internships, and the Job Ready Program for the applicants!

DataMites Data Analytics Certificate states that you have completed coursework in a Data Analytics domain; it does not imply that you have a particular skill set. Our Certified Data Analyst Course Fee in Ghaziabad is 55,000 INR, but it's currently on sale for 44,900 INR. IABAC and JainX have certified it

Ghaziabad, formerly Ghaziuddin Nagar, is a city in the state of Uttar Pradesh. The IT sector has grown in Ghaziabad, which is located east of Delhi, in recent years. Many industries in Ghaziabad are contributing to the city's development as an industrial paradise for all investments and future growth. 

Almost no brand nowadays can be found without a social media presence, and soon every business will require data analytics specialists, making it a bright career choice with the prospective for success in business. The data analyst in Ghaziabad earns an average amount of 3,65,000 LPA! (Payscale) Take up the Data Analytics Training in Ghaziabad!

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 Ghaziabad.

ABOUT DATA ANALYTICS COURSE IN GHAZIABAD

The science of studying unstructured data in order to draw inferences about it is known as data analytics. Numerous data analytics approaches and procedures have been mechanised into mechanical procedures and algorithms that analyse raw data for human consumption.

In the fields of engineering, computer science, and management, there are postgraduate courses in data science accessible. A Bachelor's degree with at least 50% overall or an equivalent grade from a reputable university, ideally in the fields of science or computer science, is the minimum requirement for enrollment in a data analytics course.

One of the most sought-after careers in 2022 will be data analysis. India is the second major centre for data-related employment after the United States. Depending on the training level you want, there will be a difference in cost. The cost of data analytics training in Ghaziabad might be anything between 30,000 and 100,000 Indian rupees.

For a position as a data analyst, a degree is not usually necessary, but obtaining the necessary certification from an approved college is essential. Acquire the skills required for success in data analytics, it can take anything from six weeks to two years. An effective method to learn about and become skilled at data analytics is to take the DataMites 4-month data analytics training course. The variety is explained by the fact that there are numerous unique routes one might take to become a data analytics professional.

If you're new to the field of data analysis, your first role can be as a junior analyst. If you've had any previous experience and have some transferrable analytical skills, you might be able to get work as a data analyst. 

  • Business Intelligence Analyst

  • Data Analyst

  • Data Scientist

  • Data Engineer

  • Quantitative Analyst

  • Marketing Analyst

  • Project Manager

  • IT Systems Analyst

  • Data Analyst Consultant

  • Operations Analyst

The benefits of a career in data analytics won't manifest without extensive training and effort. Data analysts require a particular set of skills to succeed in their line of work, and while having a technical background is important, they also need a few soft skills.

  • Data Clearing and Information Display

  • Linear algebra, MATLAB, R, Python, and NoSQL Machine Learning Calculus

  • Communication and Critical Thinking in Excel for Windows

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

Salary packages will undoubtedly remain attractive to qualified candidates as the supply of talent is running low, as we previously stated. Compared to other IT careers, switching to a data analytics career has far more financial advantages. The data analyst in Ghaziabad earns an average amount of 3,65,000 LPA! (Payscale)

There are many outstanding work prospects in this industry because there is a growing need for data specialists and a limited supply. The ideal place 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 practical experience!

The phrase "data analytics" has become more popular today due to the rise in data generation. As the curriculum is designed to train applicants from level 1, there are no formal prerequisites for the DataMites Data Analytics Course in Ghaziabad. However, having prior understanding of programming languages, databases, data structures, mathematics, and algorithms will only be advantageous.

The Certified Data Analyst Course in Ghaziabad, which validates your ability to confidently evaluate data using a variety of technologies, is the highest credential in data analytics. A certification shows that you are competent in handling data, doing exploratory research, understanding the foundations of analytics, and visualising, presenting, and elaborating on your findings. IABAC and the famous Jain University both acknowledge the DataMites Certified Data Analyst Training in Ghaziabad.

The finest training in the field is the DataMites data analyst certification programme in Ghaziabad. Our data analytics course equips you with the tangible evidence you need to prove your suitability for helping organisations, including renowned international corporations, interpret the data at hand. It is evidence that you are qualified to carry out the responsibilities of a particular work role in accordance with industry standards, as opposed to a data analytics certification.

Yes, however, it doesn't need highly developed programming abilities. The fundamentals of Python or R must be mastered, as must expertise in a querying language like SQL. Fortunately, learning the fundamentals of these languages is simple. There is nothing DataMites cannot teach you.

Although both business analytics and data analytics have their own significance, there are some essential differences between them. Data analytics is the process of examining databases to determine the data they contain. You can take raw data and find patterns using data analysing tools to gain insightful knowledge. Business analytics is a practical use of statistical analysis that focuses on giving suggestions that can be put into practise.

There are myriad things to secure your debut job in this in-demand industry, and data analytics jobs may be found in a broad range of sectors. DataMites is intended to help you upskill so that you may become a data analytics professional, whether you're just starting out in the professional world or switching to a new field.

View more

FAQ’S OF DATA ANALYTICS TRAINING IN GHAZIABAD

Both amateurs and experts are welcome to enrol in the training. The best option for you if you want to switch from an IT to a business profile is a profession as a data analyst. You will be well-suited to succeed in this industry if you are skilled in coding and IT. Anyone is welcome to enrol in DataMites Training, including those who perform in the banking, human resources, marketing, or sales sectors.

DataMitesTM is a global institute for data science that has received approval from the International Association of Business Analytics Certifications (IABAC).

  • more than 50,000 candidates were trained

  • The three-phase learning technique was painstakingly constructed to deliver the best training possible.

  • Participate in worthwhile initiatives and case studies.

  • Get the JainX Data Analytics Certification and the global IABAC certification.

  • Assistance finding internships and jobs

The completion of data analytics training and achievement of certified data analytics specialist status have various advantages in a data-driven environment. Training in data analytics will be provided to you by DataMites for four months.

One of DataMites' top data analytics programmes, the Certified Data Analyst curriculum, has been acknowledged by the illustrious organisations IABAC and JainX, whose credentials you would earn upon successfully completing the programme. Earning the DataMites Certified Data Analyst Training in Ghaziabad is encouraged to launch a career in data analytics.

Data analytics has become a broad topic, thus we wish to train informed experts in it. DataMites' instructors are very knowledgeable and have practical expertise in the data industry, so they can offer the best learning environment for your future significant step.

For a period of three months, participants in our Flexi-Pass for Data Analytics Certification Training in Ghaziabad are allowed to attend sessions led by Datamites that are pertinent to any question or revision they wish to pass.

You'll surely receive a certificate of completion for your data analytics course in Ghaziabad when it's all said and done.

We do provide on-demand classroom instruction at your facility. Although you can study from anywhere in the world with the help of our instruction, you won't need to adhere to a strict timetable or commute from one location to another. There are benefits to self-paced learning with a curriculum that is just as useful as in-person instruction.

Carry your valid Photo documents, such as a passport or driver's licence, when you register for the certification exams and receive your participation certificate.

Three stages of learning are offered by DataMites. For self-study in Phase 1, candidates will be given books and videos to assist them learn everything they need to know about the programme. The first part of the intensive live online training is Phase 2, and after you complete it, you'll obtain the IABAC Data Analytics Certification, a universal credential. And we'll assign projects and placements in the third phase.

The DataMites Data Analytics Training is scrupulously developed and structured in this way so that newcomers to the field are given a thorough overview of the entire subject. You can sign up right away if learning analytics appeals to you.

Yes, after the course is finished, our dedicated Placement Assistance Team (PAT) at DataMites will offer you placement services, including help finding a job and interview preparation.

We take payments using; 

  • 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.

View more

OTHER DATA ANALYTICS TRAINING CITIES IN INDIA

Global DATA ANALYTICS COURSES Countries

popular career ORIENTED COURSES

DATAMITES POPULAR COURSES


HELPFUL RESOURCES - DataMites Official Blog