DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN FIJI

Live Virtual

Instructor Led Live Online

FJD 4,200
FJD 2,377

  • 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

FJD 2,100
FJD 1,362

  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

Corporate Training

Customize Your Training


  • Instructor-Led & Self-Paced training
  • Customized Learning Options
  • Industry Expert Trainers
  • Case Study Approach
  • Enterprise Grade Learning
  • 24*7 Cloud Lab

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UPCOMING DATA ANALYST ONLINE CLASSES IN FIJI

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 ANALYST COURSE

Why DataMites Infographic

SYLLABUS OF DATA ANALYST COURSE IN FIJI

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 Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators

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
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS

• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions

MODULE 1 : OVERVIEW OF STATISTICS 

  • Introduction to 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
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • 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 & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of Hypothesis testing

MODULE 1: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis

MODULE 2: VARIANCE AND FREQUENCY ANALYSIS

• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for 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: Manufacturing

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• 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

MODULE 7: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity

MODULE 2: OPTIMIZATION MODELS

• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel

MODULE 4: DECISION MODELING

• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer

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;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool

MODULE 4: ML ALGO: KNN

• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool

MODULE 5: ML ALGO: K MEANS CLUSTERING

• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering

MODULE 6: ML ALGO: DECISION TREE

• Decision Tree and How it works
• 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
• Hands-on: SVM with ML Tool

MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)

• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool

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

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
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank

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

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

MODULE 1: TABLEAU FUNDAMENTALS

• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies

MODULE 2: POWER-BI BASICS

• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION

MODULE 3: DATA TRANSFORMATION TECHNIQUES

• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES

• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model

OFFERED DATA ANALYST COURSES IN FIJI

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN FIJI

Embark on the fascinating realm of Data Analytics, a field witnessing exponential growth globally. The data analytics market, valued at USD 49.08 billion in 2022, is projected to exceed USD 524.44 billion by 2032, boasting a remarkable CAGR of 26.73% from 2023 to 2032. In Fiji, the Data Analytics industry is rapidly gaining momentum, aligning with global trends. Explore the opportunities unfolding in Fiji's tech landscape, as businesses recognize the value of data-driven insights, making it an exciting hub for the burgeoning field of Data Analytics.

DataMites emerges as a leading institute, providing comprehensive training in the field. Positioned as a global training institute, DataMites offers a Certified Data Analyst Course in Fiji tailored for beginners and intermediate learners in Fiji. This career-oriented program ensures a robust foundation in data analysis, data science, statistics, visual analytics, data modeling, and predictive modeling. Accredited with IABAC Certification, the course stands as a testament to our commitment to fostering skill development in the dynamic field of Data Analytics.

At DataMites, we unfold a meticulously structured Certified Data Analyst Training in Fiji in three phases, catering to aspiring data analysts in Fiji:

Phase 1: Pre Course Self-Study

Embark on your learning journey through high-quality videos, employing an easy-to-understand approach.

Phase 2: 3-Month Duration

Dive into live training sessions, dedicating 20 hours weekly to a comprehensive syllabus. Engage in hands-on projects under the guidance of expert trainers and mentors.

Phase 3: 3-Month Duration

Advance your skills through project mentoring, completing 5+ capstone projects, experiencing real-time internships, and contributing to a live client project. Obtain IABAC and data analytics internship certifications, ensuring a well-rounded and practical learning experience.

Certified Data Analyst Courses in Fiji - Features

  1. Leadership Excellence: Ashok Veda, with over 19 years in Data Analytics and AI, leads our top-tier education.
  2. Program Structure: No-Code Program over 6 months, 20 hours of weekly learning, and 200+ learning hours.
  3. Global Certification: Attain IABAC® Certification, showcasing your proficiency globally.
  4. Flexible Learning: Seamlessly blend learning with online Data Analytics courses in Fiji and self-study.
  5. Practical Exposure: Dive into projects with real-world data, including 5+ capstone projects and 1 client/live project.
  6. Career Support: Benefit from end-to-end job support, personalized resume and interview preparation, and continuous job updates.
  7. Learning Community: Join an exclusive community fostering collaboration and shared knowledge.
  8. Affordable Pricing: Explore budget-friendly options with data analytics course fees in Fiji ranging from FJD 965 to FJD 2969.

Fiji's Data Analytics sector is flourishing, embodying a burgeoning space for technological innovation and insights derived from data. The industry reflects a commitment to advancing analytics practices, contributing to Fiji's digital evolution.

Data Analysts in Fiji enjoy substantial remuneration, with an average yearly salary of 51,600 FJD, as reported on Glassdoor. This robust compensation is indicative of the high demand for skilled professionals in Fiji's Data Analytics landscape. Their pivotal role in deciphering complex data is not only valued but rewarded generously, positioning Data Analysts as highly paid contributors to Fiji's progressive and thriving Data Analytics industry.

Embark on a transformative journey with DataMites in Fiji, where our commitment to excellence is reflected in the thriving Data Analytics landscape. Beyond our Data Analytics Training in Fiji, we offer a spectrum of courses encompassing Python, Data Engineering, Tableau, Data Science, Machine Learning, Artificial Intelligence, and more. Each program is meticulously designed to shape aspiring professionals into industry-ready experts. Choose DataMites as your trusted partner for career success, where knowledge meets opportunity, and chart a rewarding path in Fiji's dynamic and growing tech ecosystem.

ABOUT DATAMITES DATA ANALYST COURSE IN FIJI

Big data analytics involves analyzing large and complex datasets to uncover insights, patterns, and trends. It utilizes advanced techniques to process and extract value from massive volumes of data, often characterized by volume, velocity, and variety, to inform decision-making and drive innovation across various industries.

Data analytics is the process of examining datasets to derive actionable insights and inform decision-making. It encompasses techniques such as statistical analysis, data mining, and machine learning to uncover patterns and trends within data, facilitating informed decision-making.

While significant progress can be made in learning data analytics within six months with dedication and focused learning, mastery often requires ongoing practice and real-world experience. However, foundational knowledge and skills can certainly be acquired in this timeframe.

Data analysts are tasked with collecting, processing, and analyzing data to generate insights. They clean and organize datasets, perform statistical analysis, create visualizations, and communicate findings to stakeholders, contributing to informed decision-making and strategy formulation.

Key job roles in data analytics include data analyst, data scientist, business analyst, data engineer, and machine learning engineer. Each role specializes in different aspects of data collection, analysis, interpretation, and application, contributing to organizational goals.

Typically, a background in mathematics, statistics, or computer science is preferred for enrolling in a data analyst course. Proficiency in programming languages and familiarity with data analysis tools may also be required for entry into such courses.

Important tools in data analytics include programming languages (Python, R), statistical packages (Pandas, NumPy), data visualization tools (Matplotlib, Seaborn), and database querying languages (SQL). Familiarity with machine learning libraries and data manipulation tools is also beneficial for comprehensive learning.

Technological advancements like artificial intelligence, big data processing, and cloud computing are shaping the future of data analytics. These advancements enable faster processing, deeper insights, and automation of tasks, leading to greater efficiency and innovation in data-driven decision-making.

Data analytics presents challenges due to the complexity of datasets, the need for advanced analytical and programming skills, and the requirement to derive actionable insights from data. Additionally, staying updated with evolving technologies and methodologies adds to the ongoing challenge of mastering data analytics.

Data Analytics Internships offer hands-on experience with real-world data sets, tools, and methodologies, crucial for applying theoretical knowledge. They provide exposure to industry practices, mentorship, and networking opportunities, accelerating skill development and enhancing employability in the competitive field of data analytics.

While coding is essential in data analytics, the extent varies. Basic proficiency in languages like Python or R is necessary for data manipulation and analysis. Extensive coding may be required for algorithm development, depending on the complexity of tasks.

DataMites, a respected institution in Fiji, provides high-quality data analytics courses like Certified Data Analyst Training - No coding. Their emphasis on practical learning and industry relevance equips students with essential skills for a thriving data analytics career.

Practical applications include predicting customer behavior for targeted marketing, optimizing supply chain logistics, detecting fraud in financial transactions, healthcare analytics for patient diagnosis, and trend forecasting in financial markets.

Data analytics enables marketers to analyze customer behavior, preferences, and trends, facilitating targeted advertising, personalized messaging, and segmentation strategies. By understanding consumer insights, marketers can optimize marketing campaigns, improve customer engagement, and enhance return on investment.

Data analytics optimizes supply chain management by improving demand forecasting accuracy, inventory management, and logistics efficiency. It enables real-time tracking of shipments, identifies potential bottlenecks, and enhances supplier performance through data-driven insights, ultimately reducing costs and improving customer satisfaction.

Artificial intelligence (AI) enhances data analytics by automating processes, detecting patterns, and making predictions from large datasets. AI techniques like machine learning enable predictive modeling, anomaly detection, and natural language processing, augmenting the capabilities of data analytics for deeper insights and smarter decision-making.

Data cleaning and preprocessing involve tasks like handling missing values, removing duplicates, and standardizing formats. Steps also include outlier detection, normalization, and data transformation to ensure data quality and suitability for analysis.

Data analytics improves healthcare by enabling predictive analytics for disease prevention, personalized treatment plans, and population health management. It enhances operational efficiency through resource optimization, patient flow management, and quality assessment, leading to improved patient outcomes and cost-effective healthcare delivery.

Essential skills in data analytics include proficiency in programming languages like Python or R, statistical analysis, data visualization, critical thinking, problem-solving, and effective communication. These skills enable data analysts to manipulate and interpret data effectively to derive actionable insights.

Data Analysts in Fiji receive significant compensation, with an average annual salary of 51,600 FJD, as stated on Glassdoor.

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FAQ’S OF DATA ANALYST TRAINING IN FIJI

Beginners and intermediate learners interested in data analytics can enroll in DataMites' Certified Data Analyst Training in Fiji. The program covers key areas such as data analysis, statistics, visual analytics, and predictive modeling, preparing participants for successful careers in the field.

Embark on your data analytics journey with DataMites' Certified Data Analyst Course in Fiji, offering flexible learning formats, a curriculum designed for real-world applications, seasoned instructors, dedicated practice lab, engaged learning community, and lifetime access to resources. With opportunities for unlimited projects and placement assistance, DataMites ensures a comprehensive and impactful learning experience.

The Data Analyst Course in Fiji offered by DataMites spans 6 months, with a weekly commitment of 20 learning hours. With over 200 learning hours in total, participants gain thorough training in data analytics to succeed in the industry.

DataMites' certified data analyst training in Fiji encompasses tools such as Power BI, essential for creating interactive data dashboards and reports.

DataMites' Certified Data Analyst Course in Fiji is curated for advanced analytics and business insights, presenting a NO-CODE option for learners to delve into analytics without coding prerequisites.

The Flexi Pass for the Certified Data Analyst Course in Fiji at DataMites offers participants the freedom to structure their learning experience. With this option, learners can access course materials and attend sessions at their convenience, enabling them to balance their studies with other commitments effectively.

The pricing structure for DataMites' Data Analytics Course in Fiji ranges from FJD 965 to FJD 2969. This course offers participants comprehensive training in data analytics, ensuring they acquire essential skills and knowledge to succeed in the field and meet industry demands effectively.

Absolutely, DataMites is committed to providing support for participants to grasp data analytics course topics in Fiji. With experienced educators, interactive study resources, individualized mentorship, and a collaborative learning environment, participants receive ongoing assistance to ensure their comprehension and achievement in the program.

Participants undertaking the Certified Data Analyst Training in Fiji will explore key areas including Data Analysis Foundation, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, Database Management incorporating SQL and MongoDB, Version Control through Git, Big Data Foundation, Python Foundation, and Certified Business Intelligence (BI) Analyst.

Payment options for the Certified Data Analytics Course at DataMites in Fiji encompass cash, debit card, check, credit card, EMI, PayPal, Visa, Mastercard, American Express, and net banking.

Ashok Veda and elite mentors spearhead the Certified Data Analyst Course at DataMites in Fiji. With extensive experience in Data Science and AI, trainers offer participants invaluable insights and guidance derived from their real-world experience at leading companies and esteemed institutes like IIMs.

In its Certified Data Analyst Course in Fiji, DataMites employs a case study-focused methodology. Participants engage in analyzing real-world data sets, honing their data analysis skills through practical application. This immersive learning approach enhances understanding and equips learners with the proficiency to address complex data challenges with confidence.

In Fiji, DataMites provides data analytics courses through diverse learning methods, such as online data analytics training in Fiji and self-paced learning. Participants can attend interactive online sessions or proceed through course materials independently, providing them with the flexibility to learn according to their own pace and convenience.

In the case of missing a data analytics session in Fiji, DataMites provides recorded sessions for flexible viewing. Additionally, supplementary study materials and resources are available to help you fill in any gaps in your understanding. This ensures you stay on schedule with the course curriculum despite missing a session.

Indeed, participants completing the Certified Data Analyst Course in Fiji at DataMites will receive the prestigious IABAC Certification. This esteemed credential verifies their mastery of data analytics, elevating their professional credibility and opening doors to lucrative career opportunities in industries that value data-driven decision-making.

DataMites in Fiji structures its data analytics career mentoring sessions to offer participants personalized guidance and support. These sessions involve one-on-one meetings with experienced mentors who provide tailored advice, insights, and career development strategies to assist individuals in advancing their careers in data analytics.

Yes, DataMites' Certified Data Analyst Course is highly valuable in Fiji. It's the most comprehensive non-coding course, making data analytics accessible to individuals without technical backgrounds. With a three-month internship at an AI company, experience certificate, and prestigious IABAC Certification, participants gain industry recognition and career opportunities.

Yes, DataMites offers internships along with the Certified Data Analyst Course in Fiji. Learners benefit from exclusive partnerships with renowned Data Science companies, gaining hands-on experience. This internship opportunity enables them to apply theoretical knowledge in practical scenarios, mentored by DataMites experts, fostering professional development and industry relevance.

Yes, DataMites integrates live projects into the data analyst course in Fiji. Learners participate in 5+ capstone projects and collaborate on 1 client/live project. These practical initiatives offer firsthand experience in applying data analytics skills to real-world situations, enhancing learners' proficiency and industry competitiveness.

Participants are required to bring valid photo identification, such as a national ID card or driver's license, to training sessions. This documentation is essential for receiving the participation certificate and scheduling certification exams. It ensures proper identification and accountability throughout the training program.

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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