DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN MUMBAI

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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Enquire Now

UPCOMING DATA ANALYTICS ONLINE CLASSES IN MUMBAI

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 MUMBAI

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 MUMBAI

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN MUMBAI

A deliberately designed curriculum that displays all-around training is offered by DataMitesTM, a global institute for b. DataMites provides several adaptable learning options, including online data analytics training in Mumbai, superbly recorded sessions, and hands-on training. The European Union's IABAC, a foundation, has accredited our data analytics certification programme in Mumbai. The DataMites data analytics course fee in Mumbai is 42,000 INR. 

Here are the three thorough steps that incorporate our learning process:

  • Phase 1: Candidates will be offered given shall have adequate for self-study to enable them to finish the core curriculum while they are getting ready for the upcoming training program.

  • The IABAC Data Analytics Credential, an international certification, is included in Phase 2's major Live Intensive Training phase together with productive capstone projects.

  • Phase 3 consists of projects, internships, and the Job Ready Program.

DataMites provide the best certification programme for data analysts: the Certified Data Analyst Course in Mumbai. You may apply cutting-edge analytics tools with the knowledge and training provided by our certified data analyst programme in Mumbai. We provide you with specialised training, giving you the knowledge and abilities you need to take a step nearer to securing your career in data analytics. Our Certified Data Analyst Course Fee in Mumbai is 55,000 INR, but it is currently being offered for 44,900 INR conversely. It has certifications from IABAC & JainX.

Data analytics are becoming more and more important to the business world every day. With DataMites data analytics training in Mumbai and your degree of skill, the opportunities are limitless for a data analyst. In order to succeed in today's digitally-driven, fiercely competitive market, decision-makers need to be able to improvise, optimise, and overcome any obstacles.

Mumbai is on the verge of becoming India's fastest-growing metropolis. In the not-too-distant future, the city is expected to be home to a slew of well-known IT firms, and it could serve as a viable alternative to Mumbai for IT workers. Moreover, LinkedIn and the US Bureau of Labor had confirmed that the role of Data Analyst would be the most in-demand by 2022. 

As per Indeed, a data analyst's salary in Mumbai is 34,707 per month and Glassdoor statistics reveal that a data analyst in Mumbai earns an average amount of 5,00,000 LPA! Get yourself Data Analytics Training in Mumbai.

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

ABOUT DATA ANALYTICS COURSE IN MUMBAI

In order to find and analyse hidden patterns, relationships, trends, correlations, and anomalies as well as to support a theory or hypothesis, data analytics is the process of extracting insights from data that has been extracted, converted, and consolidated.

Anyone who wants to learn more about data science and analytics is welcome to enrol in the course. A Bachelor's degree with at least 50% overall or an equivalent grade from a reputable university, ideally in the sciences or computer science, is the minimal requirement for admission to a postgraduate Data Analytics study.

The essential function of modern firms is data analysis. Since no single data analytics tool can meet all needs, selecting the best one might be difficult. Some of the essential instruments used for data analytics are Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R, and Python.

A very solid career in data analytics. There has never been a better time to be a data professional, to put it simply. Data creation is increasing at a rate of 2.5 quintillion bytes each day. Depending on the training level you want, there will be a difference in cost. The cost of data analytics training in Mumbai might be anything between 30,000 and 100,000 Indian rupees.

Your initial employment can be a junior analyst position if you're new to the profession of data analysis. You might be able to find employment as a data analyst if you have some prior experience with transferable analytical skills.

  • Business Intelligence Analyst

  • Data Analyst

  • Quantitative Analyst

  • Data Analyst Consultant

  • Operations Analyst

  • Marketing Analyst

  • Data Scientist

  • Data Engineer

  • Project Manager

  • IT Systems Analyst

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.

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 a wide spectrum.

Data analytics is a lucrative and fiercely competitive field. It's difficult to find work in this profession, so you'll need to be very persistent if you want to succeed. Data analysts don't just appear out of nowhere. If you want to begin a career in data science as a novice, DataMites will provide you with the knowledge, experience, and understanding of the ideas.

  • 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 in the UK is £36,535 per annum.  (Glassdoor)

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

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

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

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

  • The national average salary for a Data Analyst in Switzerland is CHF 95,626 per year. (Glassdoor)

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

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

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

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 college. It can take anywhere between six weeks and two years to master the skills necessary for success in data analytics. Taking the DataMites data analytics courses in Mumbai is an efficient way to learn about and gain expertise in data analytics. The variety is accounted for by the fact that there is a wide range of distinctive paths one can take to become a data analytics professional.

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 Training in Mumbai. However, having a prior understanding of programming languages, databases, data structures, mathematics, and algorithms will only be advantageous.

The most valuable certification in data analytics is the Certified Data Analyst Course in Mumbai, 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 CDA Course.

The income growth that comes with a data analytics career is one of its profitable aspects. The pay for big data positions is rising in line with the demand for qualified data analysts. As per Indeed, a data analyst's salary in Mumbai is 34,707 per month and Glassdoor statistics reveal that a data analyst in Mumbai earns an average amount of 5,00,000 LPA!

Your greatest option in the field is the data analyst certification training in Mumbai from DataMites. 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.

Yes, however, it doesn't call for highly developed coding abilities. It is essential to be proficient in a querying language like SQL as well as the fundamentals of Python or R. These languages' fundamentals are fortunately simple to learn. You can learn this from DataMites, nothing is impossible.

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FAQ’S OF DATA ANALYTICS TRAINING IN MUMBAI

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

You may grow in your career and apply for the highest-paying opportunities with the help of data analytics training that is specifically designed for the needs of the sector. With the surge in the use of analytics, having the capacity to work with data is no longer optional. The value of these skills will only increase as more sectors and businesses jump on board.

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. DataMites Data Analytics Certification Courses in Mumbai is also open to non-IT professionals working in industries like hum an resources, banking, marketing, and sales, among others.

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

The sky is the limit for a data analyst with the appropriate training in data analytics and the necessary level of expertise on your part. You will find four months of data analytics courses at DataMites.

It may seem like there is never enough time to learn everything there is to know about a career in data analytics. Data analysts should be familiar with analytics, data visualisation, and data management tools but do not need to have sophisticated coding abilities.

The Certified Data Analyst curriculum, one of the best data analytics programmes offered by DataMites, has earned accreditation from the internationally recognised IABAC and JainX authority, whose credentials you would obtain after completing the course. The most effective method for beginning a career in data analytics is to obtain the DataMites Certified Data Analyst credential.

Complete the DataMites Certified Data Analyst Training in Mumbai without a doubt if you're thinking about working as a data analyst. We promise that our curriculum will give you the knowledge, assurance, and certifications needed to start a data analyst career from scratch.

Data analytics has grown to be a large field, so we want to train knowledgeable experts in the domain. DataMites has highly knowledgeable instructors who have hands-on expertise in the data sector. They will provide you with the greatest learning environment for your next significant endeavour.

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

If IABAC and Jain University accredit you, you will receive an IABAC® certification and a JainX certification, which will provide worldwide recognition of the necessary abilities and pave the road for your potential employment in the sector.

Yes, we do have demo sessions that are held for free and give prospective students a general summary of what the upcoming course would entail. You are welcome to attend these sessions to gain an idea of what the training will include before deciding whether to continue.

Data analytics classroom training in Mumbai helps to educate useful skills and knowledge and allows valid scope for deeper and fluent grasp on the subject matter with a stronger emphasis upon teamwork, group learning, and social interaction.

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

Unquestionably, we will give you a certificate of completion for your data analytics course in Bangalore after you complete the programme.

The three-phase learning procedure is provided by DataMites. To help candidates learn everything they need to know about the programme during Phase 1, candidates will be provided with books and self-study videos. The IABAC Data Analytics Certification, which is a global certification, is awarded at the conclusion of Phase 2, which is the primary portion of the intensive live online course. During the third phase, we will also assign tasks and places.

Payment can be made via;

  • Cash

  • Credit Card

  • PayPal

  • American Express

  • Net Banking

  • Cheque

  • Debit Card

  • Visa

  • Master 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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