## DATA ANALYST COURSE FEE IN AMMAN, JORDAN

### Live Virtual

Instructor Led Live Online

##### JOD 1,400
###### JOD 798

• 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

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### Blended Learning

Self Learning + Live Mentoring

##### JOD 700
###### JOD 450

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

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### Corporate Training

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

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## 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.

## SYLLABUS OF DATA ANALYST COURSE IN AMMAN

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
• 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

• 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
• 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
• 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

## ABOUT DATA ANALYST TRAINING IN AMMAN

In the heart of Amman, explore the transformative realm of Data Analytics. With substantial global market growth, as highlighted in Technavio's report projecting a USD 196.47 billion potential growth difference from 2021 to 2026, Amman's Data Analytics industry reflects this upward trajectory. Uncover the opportunities embedded in Amman's dynamic landscape and commence your learning journey in data analytics to capitalize on the unprecedented growth within this industry.

You can start your Data Analytics Career in Amman with DataMites, a renowned global institute. Our Certified Data Analyst Course in Amman is meticulously crafted for beginners and intermediate learners, focusing on building a career-oriented foundation. Delving into crucial areas like Data Analysis, Data Science Foundation, Statistics, Visual Analytics, Data Modeling, and Predictive Modeling, this program ensures a comprehensive learning experience. Successful candidates earn the prestigious IABAC Certification, validating their proficiency in the intricate domain of Data Analytics.

In the heart of Amman, DataMites offers a transformative Certified Data Analyst Training in Amman program structured into three pivotal phases.

1. The initial phase emphasizes pre-course self-study through high-quality videos with an accessible learning approach.
2. Following this, the three-month live training phase requires a commitment of 20 hours per week, encompassing a comprehensive syllabus, hands-on projects, and guidance from seasoned trainers and mentors.
3. The subsequent three-month phase focuses on project mentoring, engagement in 5+ capstone projects, real-time internship exposure, execution of a client/live project, and the acquisition of IABAC and data analytics internship certifications. This methodical training ensures a robust foundation and practical expertise for a successful career in Data Analytics.

Certified Data Analyst Courses in Amman from DataMites

Expert Leadership with Ashok Veda and Faculty

Led by industry veteran Ashok Veda, bringing over 19 years of expertise in Data Analytics and AI, DataMites assures top-tier education. Ashok Veda, also the Founder & CEO at Rubixe™, showcases unparalleled knowledge, providing students with an invaluable learning experience.

Comprehensive Course Curriculum - No-Code Program (Optional Python)

Our 6-month program ensures a robust education, committing 20 hours per week for a total of 200+ learning hours. With a focus on practicality, the course offers a no-code program (optional Python) and culminates in IABAC® Certification, a globally recognized achievement.

Adapt to your schedule with our online Data Analytics courses in Amman and self-study options, ensuring a flexible and accessible learning experience.

Projects with Real-World Data and Internship Opportunity

Immerse yourself in real-world applications through 5+ capstone projects and a client/live project. Our program includes a real-time data analytics courses with internship in Amman, providing hands-on experience and enhancing your practical skills.

End-to-End Career Support and Exclusive Learning Community

Benefit from comprehensive career guidance, personalized resume crafting, data analytics interview preparation, and job references. Join our exclusive learning community for networking, collaboration, and growth.

Affordable Pricing and Scholarships

Embark on this transformative journey with affordable pricing, with the data analytics training fee in Amman ranging from JOD 305 to JOD 938. Explore scholarship opportunities to make quality education accessible to all aspiring Data Analysts. DataMites is your gateway to a successful career in Data Analytics.

Amman's Data Analytics industry serves as a hub for innovation, actively contributing to the city's technological progress. With a focus on cutting-edge solutions and strategic insights, Amman positions itself as a key player in the global data analytics industry, fostering an environment conducive to data-driven decision-making.

In this dynamic environment, Data Analysts enjoy not only recognition but also competitive remuneration. According to Salary Explorer, the average annual salary for a Data Analyst in Jordon is an impressive 18,200 JOD. This substantial pay signifies the industry's acknowledgment of the crucial role Data Analysts play in driving innovation and contributing to Amman's prominence as a technological hub.

In Amman, DataMites serves as the beacon for career success, offering a spectrum of courses in python, Machine Learning, Data Science, Data Engineering, Artificial Intelligence, Tableau, and beyond. Under the guidance of industry leader Ashok Veda, our programs provide a solid foundation for career growth. Join DataMites to acquire expertise, engage with a vibrant learning community, and set yourself on the path to success in Amman's dynamic technology and analytics arena. Your journey to career excellence starts here with DataMites.

## ABOUT DATAMITES DATA ANALYST COURSE IN AMMAN

Data analytics involves systematically analyzing raw data to extract meaningful insights, patterns, and trends, utilizing various techniques and tools to inform decision-making processes.

Data analysts collect, process, and analyze data, cleaning and organizing datasets, identifying trends, creating reports, and contributing to data-driven decision-making.

Essential skills include proficiency in programming languages (e.g., Python, R), statistical analysis, data cleaning, visualization tools, and strong critical thinking and communication abilities.

Common roles include data analyst, business intelligence analyst, data scientist, and machine learning engineer, each specializing in different aspects such as descriptive analytics or predictive modeling.

Data visualization enhances analytics by presenting complex information visually, simplifying interpretation for analysts and stakeholders through graphs, charts, and dashboards.

The horizon for data analysis appears bright, fueled by advancements in AI, machine learning, and big data. As industries increasingly embrace data-driven decision-making, the demand for skilled data professionals is expected to surge.

Essential tools for aspiring data analysts include programming languages like Python and R, alongside data visualization tools such as Tableau or Power BI. Proficiency in SQL for database querying and Excel for statistical analysis are also fundamental.

Data analytics presents challenges due to its interdisciplinary nature, requiring proficiency in statistics, programming, and domain-specific knowledge. However, with dedication and appropriate resources, learners can overcome these challenges and excel in the field.

Data analytics primarily involves extracting insights from existing datasets using descriptive and diagnostic analytics techniques. In contrast, data science encompasses a broader spectrum, incorporating predictive modeling, machine learning, and advanced analytics to derive insights and develop predictive models.

In marketing, data analytics is pivotal for analyzing customer behavior, preferences, and demographics. It aids in optimizing advertising strategies, personalizing campaigns, and evaluating marketing effectiveness, empowering businesses to make data-driven decisions for targeted and efficient marketing efforts.

Data analytics finds diverse applications across industries. For instance, in marketing, analysts leverage customer data for targeted campaigns, while in healthcare, analytics aids in optimizing patient care through predictive modeling and trend analysis.

While full proficiency varies, individuals with a structured learning plan, consistent effort, and appropriate resources can establish a solid foundation in data analytics within a six-month timeframe.

According to Salary Explorer, the average yearly salary for Data Analysts in Amman stands at an impressive 18,200 JOD.

Internships provide invaluable real-world experience, enabling aspiring data analysts to apply theoretical knowledge in professional settings. This hands-on learning bridges the gap between academic study and the practical skills demanded in the workplace.

Coding is fundamental to data analytics, particularly with languages like Python and R. Proficiency in coding enhances data manipulation and analysis capabilities, although the level of coding required varies among roles within the field.

Advancements like AI and machine learning are revolutionizing data analytics, enabling automation, enhanced algorithms, and real-time decision-making. These innovations propel data analytics to a central position across industries, facilitating more sophisticated analysis and predictive modeling.

DataMites stands out as a premier institution providing quality data analytics courses in Amman. Their curriculum emphasizes practical, industry-relevant skills, empowering students for success in the dynamic field of data analytics.

SQL, or Structured Query Language, is a specialized language used primarily for managing and querying databases. It's a subset of data analytics, focusing specifically on tasks related to structured data management.

In retail, data analytics optimizes inventory management, forecasts demand, and analyzes customer behavior. Retailers leverage data to refine pricing strategies, tailor customer experiences, and streamline supply chain operations.

Typically, individuals enrolling in data analyst courses possess a bachelor's degree in statistics, mathematics, computer science, or related fields. These backgrounds provide foundational knowledge essential for understanding data analysis principles.

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## FAQ’S OF DATA ANALYST TRAINING IN AMMAN

The Data Analyst Course offered by DataMites in Amman spans 6 months, requiring students to allocate 20 hours per week for learning. With over 200 hours of instruction, participants acquire essential skills in data analysis to excel in the field.

Opting for DataMites' Certified Data Analyst Course in Amman brings numerous advantages. Notable features include flexible learning arrangements, a curriculum aligned with industry requirements, expert instructors, access to an exclusive Practice Lab, and a supportive learning environment. Furthermore, students enjoy lifetime access, diverse project opportunities, and comprehensive placement assistance, making it a premier choice for those pursuing a career in data analytics.

DataMites' Certified Data Analyst Training in Amman is tailored for novices and those with intermediate knowledge in data analytics. This career-centric program offers a robust understanding of data analysis, data science, statistics, visual analytics, data modeling, and predictive modeling, addressing the needs of individuals aiming for positions in the data analytics sphere.

DataMites' Certified Data Analyst Course in Amman is tailored for advanced analytics and business insights. It's a No-Code program, allowing data analysts and managers to master advanced analytics without programming prerequisites. Participants can choose optional Python training. The course content is regularly updated to align with industry standards, facilitating a structured learning journey for efficient skill acquisition.

DataMites' Data Analytics Course in Amman is priced between JOD 305 and JOD 938, catering to diverse budgets and requirements. With this range, individuals can choose a package that aligns with their learning objectives and financial considerations, ensuring accessibility to quality data analytics education.

Yes, DataMites is committed to assisting you in understanding data analytics course in Amman. Our support system comprises experienced professionals who offer guidance and clarification on course material, ensuring your comprehension and success in mastering data analytics concepts.

In DataMites' certified data analyst training in Amman, participants gain proficiency in a diverse set of tools such as Advanced Excel, MySQL, MongoDB, Git, GitHub, Atlassian BitBucket, Hadoop, Apache Pyspark, Anaconda, Google Collab, Numpy, Pandas, Tableau, and Power BI.

In Amman, DataMites provides data analytics courses featuring versatile learning options, including Online Data Analytics Training in Amman or Self-Paced Training, empowering participants to tailor their learning journey according to their needs and pace.

Topics in the Certified Data Analyst Training in Amman include Data Analysis Fundamentals, Statistics Essentials, Data Analysis Associate, Advanced Data Analytics, Predictive Analytics with Machine Learning, SQL and MongoDB Databases, Git Version Control, Big Data Foundations, Python Fundamentals, and Certified Business Intelligence (BI) Analyst skills.

DataMites in Amman accepts various payment methods for its Certified Data Analytics Course, including cash, debit card, check, credit card (Visa, Mastercard, American Express), EMI, PayPal, and net banking, ensuring ease and accessibility for participants.

DataMites' Flexi Pass for the Certified Data Analyst Course in Amman provides learners with the flexibility to tailor their study hours and pace, accommodating busy schedules and personal commitments.

Yes, upon finishing the Certified Data Analyst Course in Amman, aspirants will earn IABAC Certification, affirming their competence in data analytics and bolstering their professional credentials.

The Certified Data Analyst Course in Amman by DataMites employs a case study-based approach, enabling hands-on learning and practical application of concepts for enhanced skill development.

In case of missing a data analytics session in Amman, DataMites provides access to session recordings, enabling you to review the content at your convenience. You can also reach out to instructors for any clarifications or utilize additional resources for self-study.

Remember to carry a valid photo ID like a national ID card or driver's license to data analytics training sessions. This is crucial for receiving your participation certificate and scheduling certification exams promptly. Your preparedness is appreciated.

Absolutely, DataMites in Amman offers live projects alongside the data analyst course, featuring 5+ capstone projects and 1 client/live project. These opportunities allow participants to apply their learning in real-world scenarios, enhancing their proficiency and readiness for the workforce.

Data analytics career mentoring sessions in Amman are structured to offer individualized guidance and support. They involve personalized coaching sessions with experienced mentors, career assessments, goal setting exercises, skill enhancement plans, networking opportunities, and continuous assistance to empower participants in achieving their career objectives.

Yes, DataMites' Certified Data Analyst Course is highly esteemed in Amman for its comprehensive curriculum tailored for non-technical individuals. With a 3-month internship experience in an AI Company, an experience certificate, and prestigious IABAC Certification, participants receive exceptional training from expert faculty, making it invaluable for career advancement.

Indeed, DataMites in Amman provides internships as part of the Certified Data Analyst Course. Through collaborations with prominent Data Science firms, learners have the opportunity to apply theoretical knowledge in practical settings. With guidance from DataMites experts and mentors, participants gain hands-on experience, enhancing their skillset and employability.

In Amman, DataMites' Certified Data Analyst Course is spearheaded by Ashok Veda and accomplished Lead Mentors renowned for their expertise in Data Science and AI.

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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