DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN KOCHI

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 KOCHI

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 KOCHI

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 KOCHI

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN KOCHI

DataMitesTM, a global institute for data analytics programmes, provides a thoughtfully constructed curriculum that demonstrates all-around training. DataMites offers a variety of flexible learning alternatives, featuring online data analytics courses in Kochi, brilliantly recorded sessions, and hands-on training. Our data analytics certification programme in Kochi has received accreditation from the IABAC, a foundation for the European Union. Use DataMites to get a sharp-end learning environment at a decent price. Owing to the umbrella nature of the course, candidates are taught everything from the very beginning. The cost of the data analytics course is 42,000 INR in Kochi. 

With the DataMites data analytics training in Kochi 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. Our Certified Data Analyst Course in Kochi 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 Training Fee in Kochi is 55,000 INR, but it's currently available for 44,900 INR. IABAC and JainX have certified it.

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

  • The first part, known as Phase 1, entails giving students access to videos and other tools for individual study in addition to the required study materials.

  • The interactive capstone project, online data analytics training, and the widely recognised IABAC Data Analytics Credential are all included in Phase 2.

  • The Job Ready Program, projects, and internships embody Phase 3.

The ‘Queen of Arabian Sea,’ Kochi's economy is categorised as a business economy with a strong focus on the service sector. Kochi is quickly becoming a popular IT destination in India. Kochi has become one of the country's technologies hotspots, thanks to the recent expansion in the IT sector and new infrastructure projects from the government.

Despite the fact that the position is entry-level, the salary is higher than that of experienced experts in most industries. As per Glassdoor, a data analyst's average salary in Cochin is 4,26,766 and payscale reported the data analyst in Kochi earns an average amount of 4,05,486 LPA!  Join Data Analytics Training in Kochi. Seize the opportunity!

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 Kochi.

ABOUT DATA ANALYTICS COURSE IN KOCHI

Analyzing raw data to derive useful, practical insights is the process of data analytics. Informed and motivated business decisions are then made using these insights. In order to turn nonsensical numbers into cohesive, understandable information, a data analyst will first collect raw data, arrange it, and then evaluate it.

Postgraduate courses in data science are available in the disciplines of engineering, computer science, and management. The minimal prerequisite for enrollment in a data analytics course in Kochi is a bachelor's degree with at least a 50% overall average or an equivalent grade from a respected university, ideally in the disciplines of science or computer science.

  • Analytics of data is becoming more and more of a top priority for top businesses.

  • More employment opportunities exist.

  • The pay for data analytics professionals is increasing. Big data analytics is prevalent everywhere you look.

  • The decision-making process for the business will be heavily influenced by you, and you can select from a variety of job titles.

The field of data analytics is tremendously rewarding. Simply put, there has never been a more favourable time to work in the data industry. Every day, 2.5 quintillion bytes of data are produced, and this rate is only increasing. Depending on the degree of instruction you want, the cost will change. The Data Analytics Training Fee in Kochi can vary between 30,000 and 100,000 Indian rupees.

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 DataMites 4-month data analytics course in Kochi 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 outlook for data analysts' employment is very good given the high need for data analytics.

  • Business Intelligence Analyst

  • Data Analyst Consultant

  • Operations Analyst

  • Data Analyst

  • Data Scientist

  • Data Engineer

  • Quantitative Analyst

  • Marketing Analyst

  • Project Manager

  • IT Systems Analyst

Modern businesses often analyse their data. Since no solution can meet all needs, selecting the best data analytics tool can be difficult. Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R, and Python are just a few of the vital tools used for data analytics.

Although both business analytics and data analytics have their own significance, there are some fundamental differences between the two. The process of examining databases to determine the data they contain is known as "data analytics." Using data analysis tools, you can take raw data and look for patterns to gain insightful knowledge. Business analytics is a practical use of statistical analysis that focuses on giving useful suggestions.

One of the most in-demand occupations worldwide is skilled data analysis. Data analysts command high wages and fantastic benefits, even at the entry level, because demand for their services is so high and the pool of qualified candidates is so small.

  • he 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 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 INR 6,00,000 per year in India. (Glassdoor)

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

One of its pleasant characteristics is the increase in income that comes with a career in data analytics. As there is a greater need for qualified data analysts, big data positions are paying more. As per Glassdoor, a data analyst's average salary in Cochin is 4,26,766 and payscale reported the data analyst in Kochi earns an average amount of 4,05,486 LPA!

 If you want to pursue a career in the analytics industry, DataMites is the finest place for you. The primary mentors are knowledgeable and industry-oriented, and the course curriculum is skillfully laid out. With projects and internship opportunities, we provide practical training!

Data analytics is a concept that has gained popularity in recent years due to the growth in data generation. Although there are no formal prerequisites for the DataMites Data Analytics Course because it is designed to train candidates starting at level 1, having prior knowledge of programming languages, databases, data structures, mathematics, and algorithms only serves to be desirable.

The most prestigious qualification in data analytics is the Certified Data Analyst designation, which attests to your competence in confidently evaluating data utilising a range of technologies. A certificate demonstrates your proficiency in handling data, conducting exploratory research, comprehending the fundamentals of analytics, and visualising, presenting, and elaborating on your findings. The DataMites Certified Data Analyst Course in Kochi is recognised by IABAC as well as the renowned Jain University.

Your greatest option in the field is the DataMites data analyst certification course in Kochi. Our data analytics course provides you with concrete proof that you are qualified to help companies, including well-known multinationals, interpret the data at hand. It is evident that you are qualified to carry out the responsibilities of a particular employment role in accordance with industry standards, as opposed to a data analytics certificate.

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FAQ’S OF DATA ANALYTICS TRAINING IN KOCHI

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 Courses in Kochi are also open to non-IT professionals working in industries like human resources, banking, marketing, and sales, among others.

For the record, DataMites' online data analytics training in Kochi is just as beneficial as its in-person counterpart. In addition to gaining knowledge from their assignments, students can improve their time management skills, which in turn allows for more contact and feedback between you and your tutor. Online education is frequently cheaper than classroom instruction.

  • The International Association of Business Analytics Certifications has recognised DataMitesTM as the world's leading institute for data science (IABAC).

  • has educated more than 50,000 candidates

  • Specifically created to deliver the greatest instruction possible, the three-phase learning approach.

  • Participate in worthwhile case studies and practical projects.

  • Take the global certification exam for IABAC and JainX Data Analytics.

  • Job and Internship Support

The cost of data analytics training in Kochi at DataMites will be roughly 42,000 INR.

By enrolling in data analytics courses designed especially for the sector, you can advance your career and apply for the best-paying jobs. You would receive a 4-month data analytics training programme at DataMites.

You should definitely finish the DataMites Certified Data Analyst Training in Kochi if you're thinking about working as a data analyst. Our programme promises to offer the knowledge, assurance, and credentials necessary to start a career as a data analyst from scratch.

One of the top data analytics programmes offered by DataMites is the Certified Data Analyst curriculum, which has been accredited by the IABAC and Jain University international recognised agencies, whose credentials you would obtain after completing the course. The best way to start a career in data analytics is to obtain the DataMites Certified Data Analyst Course in Kochi.

You have a variety of learning options with DataMites, including data analytics training online in Kochi, self-study courses, and classroom training in data analytics. Every training session is designed to help participants flourish in the field.

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 duration of three months, candidates may follow Datamites sessions related to any question or revision they wish to clearing with our Flexi-Pass for Data Analytics Certification Training.

Your IABAC® certification and JainX certification, which provide global recognition of the essential abilities and pave the road for your future employment in the industry, will be given to you once you have been accredited by IABAC and Jain University.

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.

We take payments using; (Kochi)

  • Cheque

  • Cash

  • Credit Card

  • Visa

  • Master Card

  • American Express

  • PayPal

  • Net Banking

  • Debit Card

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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