DATA ANALYTICS CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYTICS COURSE FEE IN TRIVANDRUM

Live Virtual

Instructor Led Live Online

110,000
57,855

  • 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
33,155

  • 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
62,605

  • 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 TRIVANDRUM

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 TRIVANDRUM

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 TRIVANDRUM

DATA ANALYTICS TRAINING REVIEWS

ABOUT DATA ANALYTICS TRAINING IN TRIVANDRUM

DataMites is an international provider of data analytics training in Trivandrum that offers specialised training in subjects like data science, machine learning, deep learning, artificial intelligence, the internet of things, and python learning. We at DataMites are proud to announce that the International Association for Business Analytics Certification (IABAC), a highly respected and esteemed organisation in the analytics industry, has approved our courses. DataMites is one of the top institutes worldwide because to its five years of strong market presence and training of over 50,000 students. The data analytics course fee in Trivandrum is 42,000 INR.

The four-month-long DataMites Data Analytics Certification Training in Trivandrum is sectioned into the classroom and online data analytics sessions and engages in a three-phase teaching technique.

Phase 1 of data analytics training is the foremost step implying the step before the training starts; distribution of and giving avenue for study materials and other resources for independent study.

The Phase 2 consists of the actual beginning of the training including the online data analytics training, thereafter the capstone projects for imminent practical expertise in the subject matter. The IABAC Data Analytics Certification in Trivandrum is also given!

Phase 3 is set apart through projects, internships, and the Job Ready Program for the candidates enabling total exposure and mastery over the subject! 

You acquire organised, logical knowledge of all the key areas of data analytics by taking structured data analyst certification course in Trivandrum. The cost of our Certified Data Analyst Course in Trivandrum, including certifications from IABAC & JainX, is 55,000 INR, but it is currently available for 44,900 INR instead.

Almost no brand nowadays can be found without a social media presence, and soon every business will require data analytics specialists. This makes it a smart career choice with the potential for success in business. As per Payscale, a data analyst's average salary in Trivandrum is 4,64,926!

Thiruvananthapuram, commonly known as Trivandrum, is a famous city in the state of Kerala, recognised for its gorgeous and undulating terrain as well as kind hospitality. Thiruvananthapuram has risen to become India's fourth most popular IT location, thanks to fast expansion in the software industry. In recent years, the city has emerged as a rapidly growing IT and economic centre.

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 Trivandrum.

Join Data Analytics Training in Trivandrum!

ABOUT DATA ANALYTICS COURSE IN TRIVANDRUM

Data analytics is the practise of studying unprocessed data in order to derive valuable, practical knowledge. When making wise business decisions, these insights are then employed as a guide. So a data analyst will get raw data, arrange it, and then analyse it to turn it from illogical numbers into comprehensible knowledge.

There are certain key distinctions between business analytics and data analytics, despite the fact that each has its own relevance. "Data analytics" refers to the process of evaluating databases to ascertain the data they hold. You can use data analysis tools to take raw data and search for patterns in order to learn meaningful information. Business analytics is a practical application of statistical analysis that emphasises making made a significant impact.

The basic answer is everyone wants to learn data science, whether they are seasoned experts or novices. Engineers, software developers, IT specialists, and marketers can all register for DataMites data analytics courses in Trivandrum.

Absolutely not. It is always preferable to have experience with Python, Excel, and SQL. However, by starting with the fundamentals, you can undoubtedly get better.

A data analytics profession is pretty robust. Simply put, there has never been a better time to be a data professional. A whopping 2.5 quintillion bytes of data are created every day. The price will vary depending on the degree of instruction you want. Training in data analytics could cost anything from 30,000 to 100,000 Indian rupees.

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 DataMites 4-month data analytics training in Trivandrum. Data analytics careers can be pursued in a variety of ways, which accounts for the wide spectrum.

The advantages of a career in data analytics won't materialise without much training and commitment. Data analysts need a specific set of skills to thrive in their area of work, and while having a technical background is vital, they also need some soft skills.

  • Providing Clearing Data for Information

  • In addition to linear algebra, machine learning algorithms are developed in MATLAB, R, Python, and NoSQL.

  • Microsoft Excel: Critical Thinking and Communication

Data analytics provides career opportunities and transferable skills outside of the computer and digital industries. 

  • Data Analyst Consultant

  • Data Engineer

  • Project Manager

  • Quantitative Analyst

  • Business Intelligence Analyst

  • Data Analyst

  • Marketing Analyst

  • Data Scientist

  • Operations Analyst

  • IT Systems Analyst

  • 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 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 Australia is AUD 85,000 per year. (Glassdoor)

  • 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 Saudi Arabia is SAR 95,960 per year. (Payscale.com)

  • 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 UAE is AED 106,940 per year. (Payscale)

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

Given that there is a shortage of talent, as we already mentioned, salary packages will undoubtedly remain attractive for qualified individuals. The financial benefits of changing careers to data analytics are far greater than those of other IT occupations.As per Payscale, a data analyst's average salary in Trivandrum is 4,64,926!

The Certified Data Analyst Course in Trivandrum, 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 Trivandrum.

Your greatest option in the field is the data analyst certification training in Trivandrum 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 courses. 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.

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.

One of the professions with the highest demand worldwide is skilled data analysts. Data analysts command enormous salaries and top-notch benefits, even at the entry-level, because there is such a high demand for their services and a dearth of qualified candidates.

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FAQ’S OF DATA ANALYTICS TRAINING IN TRIVANDRUM

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 4-month Data Analytics Course in Trivandrum is an efficient way to learn about and gain expertise in data analytics. The variety is accounted for by the fact that there are a wide range of distinctive paths one can take to become a data analytics professional.

You may grow in your career and apply for the highest-paying opportunities with data analytics training that is specific to the needs of the sector. Having the ability to work with data is no longer optional given the surge in the use of analytics. The importance of data analytics skills will only increase as more sectors and businesses come on board.

Once you have been authorised by IABAC and Jain University, you will obtain an IABAC® certification and a JainX certification, paving the way for your future career in the industry and guaranteeing that your skills are acknowledged globally.

  • An international centre for data science called DataMitesTM has received approval from the International Association of Business Analytics Certifications (IABAC).

  • 50,000+ hopefuls were trained

  • The three-phase learning method was carefully designed to deliver the best training possible.

  • Participate in relevant case studies and initiatives that are based in reality.

  • Get certified in JainX Data Analytics and the global IABAC.

  • assistance with finding a job and an internship

Students of all experience levels are encouraged to enrol in the course. Becoming a data analyst is the finest career move for you to make if you want to go from an IT to a business profile. If you are skilled in coding and IT, you will be prepared to excel in this field. People who work in industries other than information technology, such as human resources, finance, marketing, and sales, are welcome to enrol in DataMites Data Analytics Certification Training in Trivandrum.

Because data analytics has developed into a vast discipline, we wish to educate informed individuals in it. The best learning environment for your future significant step can be provided by our instructors at DataMites because they are very skilled and have practical experience in the data sector.

We do offer ad-hoc classroom instruction in your region. Even if you don't have to commute or follow a set schedule to study with our programme, you can attend the online data analytics course in Trivandrum from anywhere in the world. There are advantages to learning on your own using a course that is just as effective as in-person tuition.

In Trivandrum, DataMites would fee about 42,000 INR for its data analytics training programmes.

By enrolling in courses in data analytics that have been built expressly for the business, you can further your career and apply for the best-paying jobs. You would undergo a 4-month training programme in data analytics from DataMites.

You has to go through the DataMites Certified Data Analyst Training if you're contemplating about working in data analysis. Our curriculum will doubtless provide the understanding, talents, and credentials needed to start a data analytics career from start to end.

The respected organisations IABAC and JainX have recognised the Certified Data Analyst curriculum, one of DataMites' top data analytics programmes, and they will provide you their credentials once you successfully complete the programme. The DataMites Certified Data Analyst Certification is recommended if you want to begin a career in data analytics.

When your course is through, you'll surely receive a degree from a data analytics training programme in Trivandrum.

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

That poses no problem for you. To set up a class that fits your schedule, talk with your trainers about the issue. You may easily catch up on the material you missed by watching the recordings and uploads of each session of the data analytics training online in Trivandrum at your own convenience and leisure. Never before has understanding data analytics been so simple!

The DataMites Data Analytics Training is skillfully planned and structured to ensure that novices to the area are given a thorough explanation of the entire domain. That being said, if understanding analytics piques your interest, you can sign up without a second thought.

A three-phase learning process is offered by DataMites. Candidates will be given books and self-study materials to use throughout Phase 1 to assist them to learn everything there is to know about the programme. The main part of the intensive live online training is Phase 2, and it culminates in the awarding of the IABAC Data Analytics Certification in Trivandrum, a universal credential. Additionally, we will assign tasks and placements during the third phase.

Working in data analytics is rewarding and hard. It can be challenging to find work in this field, and persistence is key to success. Data analysts don't just appear out of nowhere. DataMites provides you with the information, practical experience, and conceptual understanding you need, especially if you intend to start a career in data analytics as a rookie.

Yes, in fact, we do provide free demo sessions for prospective students that provide a general idea of what the forthcoming course would entail. You are welcome to attend these sessions in order to acquire a feel for the training and make a decision regarding whether to continue or not.

We accept payments using; 

  • Master Card

  • Net Banking

  • Cash

  • Credit Card

  • PayPal

  • American Express

  • Debit Card

  • Visa

  • 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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