CERTIFIED DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYTICS LEAD MENTORS

DATA ANALYST COURSE FEES IN EDINBURGH

Live Virtual

Instructor Led Live Online

1,650
932

  • 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

830
532

  • 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

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  • 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 EDINBURGH

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 CERTIFICATION IN EDINBURGH

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 EDINBURGH

DATA ANALYST TRAINING COURSE REVIEWS

ABOUT DATAMITES DATA ANALYST TRAINING IN EDINBURGH

The data analytics industry was worth $49.87 billion in 2020, and it is anticipated to expand at a compound annual growth rate (CAGR) of 18.7% during the projection period, ultimately reaching a market size of $132.9 billion by 2026, according to a report by Market Research Future.

For anyone looking to start a career in data analytics, DataMites offers a comprehensive training program that can help you get there. Our Certified Data Analyst Course in Edinburgh is designed for beginners and intermediate learners and covers a range of topics, including data science basics, statistics, visual analytics, data modeling, and predictive modeling. The program is six months long and includes two months of live online instruction, two months of real-world projects, and two months of the internship experience. Upon completion, students will have the skills and experience needed to excel in entry-level data analytics positions. DataMites Certified Data Analyst Training in Edinburgh has been endorsed by IABAC, a global organization.

Edinburgh, Scotland's capital city, has a well-established data analytics market. The city is home to several universities, including the University of Edinburgh, which has a strong reputation for research in this field. Major companies, including Amazon and Microsoft, have established data analytics teams in Edinburgh, making it an attractive location for job seekers. According to Indeed.com, the average salary for a data analyst in Edinburgh is £35,633 a year. Pursuing a data analytics course in Edinburgh offers access to a well-established market with several major companies, strong university programs, and a thriving tech scene, making it a prime location for data analysts.

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

ABOUT DATA ANALYST COURSE IN EDINBURGH

The art of data analytics involves scrutinizing and analyzing data sets to draw meaningful conclusions, identify trends, and make informed business decisions. It involves using statistical and computational methods to process and analyze data in order to uncover relevant insights that can be used to enhance operations, reduce costs, improve efficiency, or gain a competitive advantage.

Certainly, anyone with a passion for data analytics and an open mind may work in this industry. But, to succeed in a data analytics career, a certain set of abilities and expertise are needed.

Data analytics requires a solid background in mathematics and statistics. This entails having a working understanding of concepts like probability, calculus, and linear algebra. Additionally, considering that programming languages like Python and R are frequently used for data analysis, fluency in these languages is crucial. They can, however, be learned. For a successful job in data analytics, it's also crucial to have strong communication, problem-solving, and critical-thinking abilities.

Several industries and use cases, including banking, marketing, healthcare, and manufacturing, can benefit from the usage of data analytics. Large and complicated data sets are analyzed using a variety of methods and technologies, such as data mining, machine learning, and predictive analytics.

  • For leading firms, data analytics is a crucial ability.
  • Expanding employment options
  • Increasing salaries for data analytics experts
  • Big Data analytics is prevalent everywhere.
  • There are countless career options.
  • In business, decision-making will revolve around you.

The fee would differ from institute to institute and the level of training you are looking for. The Data Analytics training fee in Edinburgh ranges from 348.14 GBP to 895.21 GBP.

According to Indeed.com, the average salary for a data analyst in Edinburgh is £35,633 a year. 

If you want to pursue a career in the analytics industry, DataMites is the finest provider 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!

The most valuable certification in data analytics is the Certified Data Analyst Course in Edinburgh, which attests to your competence in confidently evaluating data utilizing a variety of technologies. Your competence in handling data, doing exploratory research, understanding the fundamentals of analytics, and visualizing, presenting, and expanding your findings are all demonstrated by your certification. 

Data analysts are needed in every business and hold a variety of positions. The usual industries are retail, healthcare, banking and finance, transportation, education, building, and technology. To name a few, you can work in data analytics, data science, business intelligence analysis, data engineering, quantitative analysis, data consulting, operations analysis, marketing analysis, project management, IT systems analysis, and transportation logistics.

FAQ’S OF DATA ANALYST COURSE IN EDINBURGH

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

  • The International Association of Business Analytics Certifications has approved the global institute for data science known as DataMitesTM (IABAC).
  • Around 50,000 candidates have been trained in data science and analytics by DataMites.
  • In order to provide the finest training possible, we adhere to a three-phase learning process.
  • Have the chance to work on actual projects and extremely useful case studies.
  • Get the international certification known as IABAC Data Analytics Certification.
  • Possibility of working as an intern for AI startup Rubixe, a leading technological company.

Anyone interested in pursuing a career in data analytics or data science can participate in the Certified Data Analyst Course because it is a No-Coding Course. The DataMites Data Analytics Training in Edinburgh is methodically planned and structured to ensure that novices to the subject are given a thorough explanation of the entire topic. That being said, if understanding analytics piques your interest, you can sign up without a second thought.

One of the top data analytics programs offered by DataMites is the Certified Data Analyst curriculum, which has been authorized by the IABAC, an internationally recognized body 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.

You will receive six months of data analytics training from DataMites, including 20 hours of instruction every week.

Complete the DataMites Certified Data Analyst Training 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.

Depending on the type of training you choose, DataMites' certified data analytics training costs can change. The cost of a certified data analytics course in Edinburgh, however, can normally range from 348.09 GBP to 744.31 GBP.

You can pay us in cash, with a debit card, a check, a credit card, PayPal, a Visa, Mastercard, or American Express card, as well as through net banking.

We will grant you IABAC® accreditation, ensuring that the relevant abilities are acknowledged internationally.

With our Flexi-Pass for the Certified Data Analytics Training, candidates have a three-month window in which to attend sessions from DataMites pertaining to any question or revision they wish to clear.

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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