DATA ANALYST CERTIFICATION AUTHORITIES

COURSE FEATURES

DATA ANALYST LEAD MENTORS

DATA ANALYST COURSE FEE IN NORWAY

Live Virtual

Instructor Led Live Online

Kr 20,370
Kr 11,561

  • 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

Kr 10,190
Kr 6,620

  • 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 NORWAY

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 NORWAY

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 NORWAY

DATA ANALYST COURSE REVIEWS

ABOUT DATA ANALYST TRAINING IN NORWAY

A Data Analyst course in Norway provides comprehensive training in statistical analysis, data visualization, and programming skills, catering to the growing demand for professionals who can extract meaningful insights from vast datasets. As per a Maximise Market Research study, the Data Analytics Market reached a valuation of USD 41.74 billion in 2022 and is projected to witness a robust growth of 29.47% from 2023 to 2029. The overall revenue for the Data Analytics sector is forecasted to achieve around USD 245.53 billion during this period.

The data analytics industry in Norway is experiencing significant expansion, aligning with worldwide patterns. The escalating digitization and growing demand for insights driven by data across various sectors underscore the necessity for skilled professionals who can fully harness the potential of data.

DataMites, a globally acclaimed institution, is delighted to introduce an extensive 6-month Certified Data Analyst Course in Norway. This comprehensive program, spanning 200 hours, covers essential topics such as No-code, MySQL, Power BI, Excel, and Tableau, offering an immersive and enriching learning experience. Notably, the institute holds international accreditation from IABAC, ensuring a globally recognized certification upon successful completion of the course. With a decade of expertise, DataMites has successfully educated over 50,000+ learners worldwide.

By delivering online data analyst training in Norway, DataMites provides invaluable insights into the field. The curriculum, enriched with internship support and projects, plays a pivotal role in enhancing students' overall career development.

DataMites provides certified data analyst training in Norway through a well-structured journey that comprises three distinct phases, ensuring a comprehensive and enriching learning experience.

The first phase commences with a self-paced pre-course study, offering participants access to high-quality, user-friendly videos to establish a robust foundation before advancing to the structured training modules.

Transitioning to the second phase, a three-month period involves intensive live training sessions, requiring a commitment of 20 hours per week. Expert trainers and mentors guide participants through a comprehensive syllabus, including hands-on projects to reinforce their learning.

The third phase, extending for another three months, emphasizes practical application. Participants actively engage in project mentoring, completing 10 capstone projects. This stage integrates real-time data analyst internship opportunities in Norway, culminating in the successful completion of a client/live project. Upon finishing this phase, participants receive IABAC and Internship Certifications.

DataMites is poised to launch its accredited data analyst course in Norway, offering an immersive learning experience enriched with distinctive features.

Leadership Excellence: Under the guidance of Ashok Veda, a seasoned professional with over 19 years in Data Analytics and AI, the program ensures expert leadership in the field, emphasizing Leadership Excellence.

Program Highlights: Noteworthy features of the course include a 6-month No-Code Program, requiring 20 hours per week, accumulating 200+ learning hours.

Certification Achievement: Upon successful completion, participants will receive the globally recognized IABAC® Certification, validating their expertise.

Flexible Learning: Flexibility is a crucial aspect of the course, providing online data analytics courses in Norway and self-study alternatives.

Practical Exposure and Hands-on Experience: The program prioritizes practical exposure and hands-on experience, with participants involved in 10 capstone projects and 1 client/live project, enhancing their skills. DataMites data analytics courses with Internship opportunities in Norway further contribute to practical expertise.

Career Support: Comprehensive career support is offered, encompassing job assistance, personalized resume crafting, data analytics interview preparation, and ongoing job updates.

Community Connection: Participants become part of an exclusive learning community, fostering collaboration and knowledge exchange.

Cost-effectiveness: The course aims to provide a cost-effective option, with data analytics course fees in Norway ranging from NOK 4,494 to NOK 13,821. This affordability makes it accessible for individuals aspiring to become data analysts.

Norway, known for its stunning fjords and vibrant Northern Lights, captivates with its breathtaking natural beauty and a rich cultural heritage deeply rooted in Viking history. The land of mountains, glaciers, and picturesque coastal towns offers a harmonious blend of outdoor adventures and serene landscapes.

The future of data analysis in Norway appears promising, as the nation continues to embrace technological advancements. With a growing demand for skilled professionals, data analysts are poised to play a pivotal role in shaping Norway's data-driven innovations across various industries. The salary of a data analyst in Norway ranges from NOK 5,11,944 per year according to a Glassdoor report.

Embark on a rewarding educational venture by enrolling in DataMites Institute's certified data analyst training in Norway. Our thoughtfully crafted curriculum ensures you acquire essential skills to excel in the dynamic realm of data analytics. Join DataMites now to establish yourself as a key contributor in the ongoing data analytics revolution, with a range of courses covering Data Science, MlOps, Machine Learning, Artificial Intelligence, Tableau, Deep Learning, Python, and Data Mining for comprehensive skill development.

ABOUT DATAMITES DATA ANALYST COURSE IN NORWAY

At its core, data analytics centers on extracting meaningful insights from data through analysis, enabling informed decision-making for businesses and organizations.

A data analyst is tasked with interpreting data, generating comprehensive reports, and effectively communicating insights to aid organizations in making informed, data-driven decisions.

Essential skills for excelling in data analytics include proficiency in statistical analysis, data visualization, programming languages like Python or R, and adeptness in database management.

Data analysts engage in various tasks, including collecting, processing, and analyzing data, as well as creating detailed reports and presenting actionable insights to facilitate informed decision-making.

The field of data analytics presents extensive opportunities across diverse industries such as finance, healthcare, marketing, and technology.

Key job roles in data analytics include Data Analyst, Business Analyst, Data Scientist, and Machine Learning Engineer, each contributing uniquely to the field.

The future trajectory of data analysis entails heightened automation, integration of AI technologies, and an escalating demand for skilled professionals adept at navigating the evolving analytical landscape.

While requirements vary, a common prerequisite for enrolling in a data analyst course is a bachelor's degree in a related field.

Critical tools for learning data analytics include Excel, SQL, Python/R programming languages, and visualization tools like Tableau.

While acknowledged as challenging, pursuing a data analytics course offers substantial rewards, requiring analytical thinking and a commitment to continuous learning.

SQL proficiency is crucial for data analysts as it enables efficient querying and manipulation of databases, facilitating effective data analysis and extraction of insights.

Yes, achieving proficiency in data analytics within six months is feasible through focused learning and practical application of skills.

The cost of the Data Analyst Course in Norway in 2024 ranges from NOK 2,000 to NOK 8,000

Certified Data Analyst courses provide industry-recognized credentials, validating skills in data analysis and enhancing professional credibility and marketability.

Internships are vital for gaining real-world experience and exposure to industry practices, facilitating practical skill development and enhancing the learning process in data analytics.

Projects enrich the learning experience in data analytics by providing opportunities to apply theoretical knowledge in practical scenarios, fostering hands-on experience and skill development.

Data analytics offers a wide array of career opportunities, including roles in data engineering, business intelligence, and data science, catering to diverse interests and skill sets.

While advantageous, proficiency in Python is not always mandatory for data analysts; however, competency in at least one programming language is recommended for effective data analysis.

Coding is an integral part of data analytics, with varying levels of involvement depending on the complexity of the analysis and the specific tasks at hand.

Yes, data analytics is universally acknowledged as a challenging field due to its multidisciplinary nature and the continuous advancements in technology, offering rewarding career prospects for those willing to invest in their skills and knowledge.

The salary of a data analyst in Norway ranges from NOK 5,11,944 per year according to a Glassdoor report.

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FAQ’S OF DATA ANALYST TRAINING IN NORWAY

DataMites distinguishes itself by offering premier data analyst certification training in Norway. The program not only equips learners with essential data interpretation skills but also provides tangible evidence of proficiency in data analytics. This certification holds significant value in the job market, making DataMites a desirable option for individuals seeking rewarding careers with multinational corporations. Moreover, beyond basic certification, DataMites' program showcases the ability to meet professional standards in specific job roles, thereby elevating its standing in the field of data analytics education.

DataMites' Certified Data Analyst Course caters to individuals with aspirations in data analytics or data science, regardless of their coding background. The course welcomes participants from all walks of life, ensuring accessibility and inclusivity. With a meticulously crafted curriculum, the program offers a comprehensive understanding of the subject matter, making it an ideal entry point for those intrigued by the analytics realm.

The Data Analyst Course offered by DataMites in Norway spans approximately six months, requiring a commitment of over 200 hours of learning. Participants are encouraged to dedicate approximately 20 hours per week to their studies, ensuring thorough exploration and comprehension of the course content.

The syllabus of the Certified Data Analyst Course in Norway includes instruction on the following tools:

  • MySQL
  • Anaconda
  • MongoDB
  • Hadoop
  • Apache PySpark
  • Tableau
  • Power BI
  • Google BERT
  • Tensor Flow
  • Advanced Excel
  • Numpy
  • Pandas
  • Google Colab
  • GitHub
  • Atlassian BitBucket 

DataMites' Data Analytics Course in Norway provides a flexible learning environment, practical curriculum, esteemed instructors, and access to an exclusive practice lab. With lifetime access, continuous growth opportunities, hands-on projects, and dedicated placement support, DataMites offers a comprehensive learning experience for aspiring data analysts.

The DataMites' Data Analytics course fee in Norway varies from NOK 4,494 to NOK 13,821. 

Yes, DataMites in Norway offers substantial one-on-one support from instructors to enhance participants' understanding of data analytics course content, ensuring an optimal learning journey.

DataMites' Certified Data Analyst Course in Norway covers a broad range of topics, including Data Analysis Foundation, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, Database: SQL and MongoDB, Version Control with Git, Big Data Foundation, and Python Foundation, culminating in the Certified Business Intelligence (BI) Analyst module.

DataMites in Norway is led by Ashok Veda, a highly esteemed Data Science coach and AI expert. The faculty includes elite mentors with hands-on experience from prestigious companies and renowned institutes like IIMs, ensuring exceptional mentorship throughout the learning journey.

The Flexi Pass for Data Analytics Course in Norway allows participants to choose batches according to their schedules, offering flexibility in training and enabling learners to customize their learning experience.

Yes, upon successful completion of DataMites' Certified Data Analyst Course in Norway, participants receive the prestigious IABAC Certification, validating their expertise in data analytics and enhancing their credibility in the industry.

DataMites adopts a results-driven approach, incorporating hands-on practical sessions, real-world case studies, and industry-relevant projects to ensure participants acquire both theoretical knowledge and practical skills essential for the dynamic field of data analytics.

DataMites provides flexibility through options like Online Data Analytics Training in Norway or Self-Paced Training, allowing participants to choose between instructor-led online sessions or self-paced learning based on their preferences and schedule.

If a participant misses a session during data analytics training in Norway, DataMites provides recorded sessions, enabling individuals to catch up on missed content at their convenience, supporting continuous learning.

To attend DataMites' data analytics training in Norway, participants need to bring a valid photo ID, such as a national ID card or driver's license, essential for obtaining the participation certificate and scheduling relevant certification exams.

In Norway, DataMites organizes personalized data analytics career mentoring sessions where experienced mentors offer guidance on industry trends, resume building, and interview preparation, focusing on individual career goals to provide tailored advice.

Yes, the Certified Data Analyst Course offered by DataMites is highly valuable in Norway, offering a comprehensive non-coding course tailored for individuals from non-technical backgrounds, including a 3-month internship, expert training, and leading to the prestigious IABAC Certification.

Yes, DataMites in Norway offers an internship alongside the Certified Data Analyst Course through collaborations with prominent Data Science companies, providing practical experience and expert guidance.

Yes, DataMites in Norway integrates live projects into the data analyst course, allowing participants to apply their skills in real-world scenarios, enhancing practical proficiency and readiness for the industry.

In Norway, DataMites accepts various payment methods, including cash, debit card, credit card (Visa, Mastercard, American Express), check, EMI, PayPal, and net banking, ensuring convenience and flexibility for participants.

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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