DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE LEAD MENTORS

DATA SCIENCE COURSE FEE IN AMMAN, JORDAN

Live Virtual

Instructor Led Live Online

JOD 1,400
JOD 901

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Live Online Training
  • 25 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

JOD 840
JOD 542

  • Self Learning + Live Mentoring
  • IABAC® & NASSCOM® Certification
  • 1 Year Access To Elearning
  • 25 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Leaner 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

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA SCIENCE ONLINE CLASSES IN AMMAN

BEST DATA SCIENCE 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 SCIENCE COURSE

Why DataMites Infographic

SYLLABUS OF DATA SCIENCE COURSE IN AMMAN

MODULE 1: DATA SCIENCE ESSENTIALS 

 • Introduction to Data Science
 • Evolution of Data Science
 • Big Data Vs Data Science
 • Data Science Terminologies
 • Data Science vs AI/Machine Learning
 • Data Science vs Analytics

MODULE 2: DATA SCIENCE DEMO

 • Business Requirement: Use Case
 • Data Preparation
 • Machine learning Model building
 • Prediction with ML model
 • Delivering Business Value.

MODULE 3: ANALYTICS CLASSIFICATION 

 • Types of Analytics
 • Descriptive Analytics
 • Diagnostic Analytics
 • Predictive Analytics
 • Prescriptive Analytics
 • EDA and insight gathering demo in Tableau

MODULE 4: DATA SCIENCE AND RELATED FIELDS

 • Introduction to AI
 • Introduction to Computer Vision
 • Introduction to Natural Language Processing
 • Introduction to Reinforcement Learning
 • Introduction to GAN
 • Introduction to Generative Passive Models

MODULE 5: DATA SCIENCE ROLES & WORKFLOW

 • Data Science Project workflow
 • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
 • Data Science Project stages.

MODULE 6: MACHINE LEARNING INTRODUCTION

 • What Is ML? ML Vs AI
 • ML Workflow, Popular ML Algorithms
 • Clustering, Classification And Regression
 • Supervised Vs Unsupervised

MODULE 7: DATA SCIENCE INDUSTRY APPLICATIONS

 • Data Science in Finance and Banking
 • Data Science in Retail
 • Data Science in Health Care
 • Data Science in Logistics and Supply Chain
 • Data Science in Technology Industry
 • Data Science in Manufacturing
 • Data Science in Agriculture

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
 • Empirical Rule and Outliers
 • Central Limit Theorem
 • Normality Testing
 • Skewness & Kurtosis
 • Measures Of Distance: Euclidean, Manhattan And Minkowski Distance
 • 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: MACHINE LEARNING INTRODUCTION 

 • What Is ML? ML Vs AI
 • Clustering, Classification And Regression
 • Supervised Vs Unsupervised

MODULE 2:  PYTHON NUMPY  PACKAGE 

 • Introduction to Numpy Package
 • Array as Data Structure
 • Core Numpy functions
 • Matrix Operations, Broadcasting in Arrays

MODULE 3:  PYTHON PANDAS PACKAGE 

 • Introduction to Pandas package
 • Series in Pandas
 • Data Frame in Pandas
 • File Reading in Pandas
 • Data munging with Pandas

MODULE 4: VISUALIZATION WITH PYTHON - Matplotlib

 • Visualization Packages (Matplotlib)
 • Components Of A Plot, Sub-Plots
 • Basic Plots: Line, Bar, Pie, Scatter

MODULE 5: PYTHON VISUALIZATION PACKAGE - SEABORN

 • Seaborn: Basic Plot
 • Advanced Python Data Visualizations

MODULE 6: ML ALGO: LINEAR REGRESSSION

 • Introduction to Linear Regression
 • How it works: Regression and Best Fit Line
 • Modeling and Evaluation in Python

MODULE 7: ML ALGO: LOGISTIC REGRESSION

 • Introduction to Logistic Regression
 • How it works: Classification & Sigmoid Curve
 • Modeling and Evaluation in Python

MODULE 8: ML ALGO: K MEANS CLUSTERING

 • Understanding Clustering (Unsupervised)
 • K Means Algorithm
 • How it works : K Means theory
 • Modeling in Python

MODULE 9: ML ALGO: KNN

 • Introduction to KNN
 • How It Works: Nearest Neighbor Concept
 • Modeling and Evaluation in Python

MODULE 1: FEATURE ENGINEERING 

 • Introduction to Feature Engineering
 • Feature Engineering Techniques: Encoding, Scaling, Data Transformation
 • Handling Missing values, handling outliers
 • Creation of Pipeline
 • Use case for feature engineering

MODULE 2: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

 • Introduction to SVM
 • How It Works: SVM Concept, Kernel Trick
 • Modeling and Evaluation of SVM in Python

MODULE 3: PRINCIPAL COMPONENT ANALYSIS (PCA)

 • Building Blocks Of PCA
 • How it works: Finding Principal Components
 • Modeling PCA in Python

MODULE 4:  ML ALGO: DECISION TREE 

 • Introduction to Decision Tree & Random Forest
 • How it works
 • Modeling and Evaluation in Python

MODULE 5: ENSEMBLE TECHNIQUES - BAGGING 

 • Introduction to Ensemble technique 
 • Bagging and How it works
 • Modeling and Evaluation in Python

MODULE 6: ML ALGO: NAÏVE BAYES

 • Introduction to Naive Bayes
 • How it works: Bayes' Theorem
 • Naive Bayes For Text Classification
 • Modeling and Evaluation in Python

MODULE 7: GRADIENT BOOSTING, XGBOOST

 • Introduction to Boosting and XGBoost
 • How it works?
 • Modeling and Evaluation of in Python

MODULE 1: TIME SERIES FORECASTING - ARIMA 

 • What is Time Series?
 • Trend, Seasonality, cyclical and random
 • Stationarity of Time Series
 • Autoregressive Model (AR)
 • Moving Average Model (MA)
 • ARIMA Model
 • Autocorrelation and AIC
 • Time Series Analysis in Python 

MODULE 2: SENTIMENT ANALYSIS 

 • Introduction to Sentiment Analysis
 • NLTK Package
 • Case study: Sentiment Analysis on Movie Reviews

MODULE 3: REGULAR EXPRESSIONS WITH PYTHON 

 • Regex Introduction
 • Regex codes
 • Text extraction with Python Regex

MODULE 4:  ML MODEL DEPLOYMENT WITH FLASK 

 • Introduction to Flask
 • URL and App routing
 • Flask application – ML Model deployment

MODULE 5: ADVANCED DATA ANALYSIS WITH MS EXCEL

 • MS Excel core Functions
 • Advanced Functions (VLOOKUP, INDIRECT..)
 • Linear Regression with EXCEL
 • Data Table
 • Goal Seek Analysis
 • Pivot Table
 • Solving Data Equation with EXCEL

MODULE 6:  AWS CLOUD FOR DATA SCIENCE

 • Introduction of cloud
 • Difference between GCC, Azure, AWS
 • AWS Service ( EC2 instance)

MODULE 7: AZURE FOR DATA SCIENCE

 • Introduction to AZURE ML studio
 • Data Pipeline
 • ML modeling with Azure

MODULE 8:  INTRODUCTION TO DEEP LEARNING

 • Introduction to Artificial Neural Network, Architecture
 • Artificial Neural Network in Python
 • Introduction to Convolutional Neural Network, Architecture
 • Convolutional Neural Network in Python

MODULE 1: DATABASE INTRODUCTION 

 • DATABASE Overview
 • Key concepts of database management
 • Relational Database Management System
 • CRUD operations

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 function: 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

MODULE 1: GIT  INTRODUCTION 

 • Purpose of Version Control
 • Popular Version control tools
 • Git Distribution Version Control
 • Terminologies
 • Git Workflow
 • Git Architecture

MODULE 2: GIT REPOSITORY and GitHub 

 • Git Repo Introduction
 • Create New Repo with Init command
 • Git Essentials: Copy & User Setup
 • Mastering Git and GitHub

MODULE 3: COMMITS, PULL, FETCH AND PUSH 

 • Code Commits
 • Pull, Fetch and Conflicts resolution
 • Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING 

 • Organize code with branches
 • Checkout branch
 • Merge branches
 • Editing Commits
 • Commit command Amend flag
 • Git reset and revert

MODULE 5: GIT WITH GITHUB AND BITBUCKET

 • Creating GitHub Account
 • Local and Remote Repo
 • Collaborating with other developers

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 SCIENCE COURSES IN AMMAN

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN AMMAN

Embarking on the captivating journey of data science, the global market showcases a substantial size, recording USD 45,941.83 million in 2021. Projections indicate a robust expansion at a CAGR of 16.29%, culminating in an estimated USD 113,603.92 million by 2027. Amidst this global surge, Amman, the vibrant capital of Amman, has solidified its presence in the data science sector. Enrolling in data science courses in Amman proves instrumental for individuals aspiring to excel in this ever-evolving domain.

DataMites emerges as a global training institute for data science, contributing significantly to Amman's dynamic data science sector. For beginners and intermediate learners in the field, DataMites offers a Certified Data Scientist Course in Amman, renowned as the world's most popular and comprehensive program. Specifically designed to be job-oriented, this course equips participants with the essential skills needed to excel in the evolving field of data science. Notably, the program also includes an IABAC Certification, adding a valuable credential to participants' profiles and ensuring their readiness for the challenges of the industry.

In the dynamic city of Amman, aspiring data scientists can benefit from DataMites' comprehensive three-phase training approach, designed to impart practical skills and knowledge.

Phase 1: Pre Course Self-Study

Before the formal training commences, participants delve into self-study. Accessing high-quality videos with an easy learning approach, this initial phase establishes a strong foundation for the upcoming training.

Phase 2: Live Training

At the heart of our program lies live training, featuring a comprehensive syllabus. Participants engage in hands-on projects, guided by expert trainers and mentors. This interactive phase ensures a thorough understanding of the nuances of data science.

Phase 3: 4-Month Project Mentoring

Following the live training, participants transition into a four-month project mentoring phase, incorporating a data science internship. This hands-on experience encompasses 20 capstone projects, culminating in a client/live project. Participants receive an experience certificate, validating their practical skills and enhancing their prospects in the job market.

In Amman, DataMites stands out with its captivating offerings, making data science training in Amman an exciting and rewarding experience.

Exceptional Leadership: Ashok Veda and Faculty

Steering our educational endeavors is Ashok Veda, a veteran with over 19 years of prowess in data science and analytics. As the Founder & CEO at Rubixe™, his leadership ensures top-notch education, providing insights from the forefront of data science and AI.

Robust Curriculum: 8-Month & 700+ Learning Hrs.

Our comprehensive course spans 8 months, offering an extensive 700+ learning hours. This thorough curriculum ensures participants gain a deep understanding of data science concepts.

Global Certification: IABAC® Certification

Upon completion, participants earn prestigious data science certifications from IABAC®, globally recognized endorsements that validate their expertise in data science.

Flexible Learning Options: Online Courses and Self-Study

Recognizing the need for flexibility, our courses provide online data science courses and self-study options, allowing participants to customize their learning journey based on their schedules.

Real-world Projects and Internship Opportunities

Our courses bring theory to life through projects using real-world data. Participants engage in 20 capstone projects and a client project, fostering active interaction and practical application of skills.

Comprehensive Career Support: End to End Job Support

DataMites goes beyond education; we offer end-to-end job support. From personalized resume and data science interview preparation to job updates and connections, we guide participants towards a successful career in data science.

Exclusive Learning Community: DataMites Community

Join our exclusive learning community, where participants can interact with peers, share insights, and stay updated on the latest trends in data science.

Affordable Pricing for Data Science 

DataMites offers affordable pricing for its data science training, with data science training fees in Amman ranging from JOD 375 to JOD 937. This cost-effective structure enables individuals to access quality data science education without compromising on curriculum depth or industry relevance. Datamites' commitment to accessible training makes it an attractive choice for aspiring data scientists.

In Amman, the data science market is flourishing, marked by a heightened recognition of the strategic importance of data analytics across various sectors. As businesses in Amman increasingly embrace data-driven decision-making, the demand for data scientists has surged, reflecting the global trajectory.

This growing significance of data science in Amman is mirrored in the compensation offered to data scientists. According to Salary Explorer, a person working as a Data Scientist in Amman typically earns around 2,940 JOD. This substantial earning reflects the value placed on the expertise of data scientists in harnessing actionable insights from complex datasets. 

Beyond our flagship Certified Data Scientist Training, we present a suite of courses encompassing Artificial Intelligence, Data Engineering, Data Analytics, Machine Learning, Python, Tableau, and more. These meticulously designed courses, guided by industry expert Ashok Veda, provide a holistic skill set, preparing professionals for the multifaceted challenges of the industry.

ABOUT DATAMITES DATA SCIENCE COURSE IN AMMAN

Data Science involves extracting meaningful insights from large datasets using techniques like statistical analysis, machine learning, and data visualization. It encompasses the entire data lifecycle, from collection and preprocessing to analysis and interpretation.

A Data Scientist's responsibilities include collecting, cleaning, and analyzing data, developing predictive models, and communicating insights to support decision-making. They play a key role in solving complex problems and driving innovation within the company.

While a bachelor's degree in a related field is common, many Data Scientists hold advanced degrees such as a master's or Ph.D. Relevant skills, experience, and a strong foundation in mathematics and programming are crucial.

Data Science unfolds by first defining the problem and collecting relevant data. It involves data preprocessing, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Collaboration and communication are integral throughout the process.

Statistics is fundamental in data science, aiding in data analysis, hypothesis testing, and model validation. It provides a robust framework for making informed decisions, drawing meaningful conclusions, and ensuring the reliability of data-driven insights.

Common challenges include data quality issues, model interpretability, and scalability. Solutions involve rigorous data preprocessing, employing explainable AI techniques, and optimizing algorithms for efficiency and scalability.

The Certified Data Scientist Course in Amman takes the lead in Amman's data science education landscape. This course imparts crucial skills, from programming to machine learning, offering hands-on training for participants to excel in the ever-evolving field of data science.

Aspiring Data Scientists need proficiency in programming languages, data manipulation, statistical analysis, machine learning, and strong communication skills. Problem-solving, critical thinking, and a continuous learning mindset are also essential for success in the field.

In Amman, a Data Scientist typically begins as an analyst, progressing to senior roles or specialized positions like machine learning engineer. Continuous learning, networking, and gaining hands-on experience contribute to career advancement.

Engaging in Data Science bootcamps proves beneficial for quick skill acquisition. These programs offer hands-on experience, mentorship, and networking, expediting entry into the field. However, the level of success relies on personal dedication and the caliber of the selected bootcamp.

Data Science in finance involves risk management, fraud detection, and customer segmentation. Predictive modeling and analytics optimize decision-making processes, enhancing customer experiences and detecting anomalies in financial transactions.

To launch a career in data science in Amman, individuals should acquire relevant educational qualifications, build a strong foundation in programming and statistics, engage in hands-on projects, and consider pursuing specialized certifications. Networking within the local data science community is also crucial.

Certification Courses for Data Science are open to individuals with backgrounds in mathematics, statistics, computer science, or related fields. Professionals seeking to enhance their analytical skills or transition into the field also find these courses beneficial.

In e-commerce, Data Science analyzes customer behavior, preferences, and transaction data to provide personalized recommendations. Machine learning algorithms power recommendation systems, tailoring user experiences, boosting engagement, and contributing to increased sales and customer satisfaction.

As per Salary Explorer, Data Scientists in Amman can expect to earn approximately 2,940 JOD annually. This reflects the standard compensation for individuals in this role, underscoring the competitive nature of salaries in Amman's data science sector

Data Science finds widespread application in industries such as finance, healthcare, e-commerce, manufacturing, and telecommunications. Its versatility empowers decision-making, enhances efficiency, and drives innovation across diverse sectors.

The data science project lifecycle comprises defining objectives, data collection, exploratory data analysis, model development, validation, deployment, and continuous monitoring. Each phase is crucial to ensuring the project aligns with business goals and delivers meaningful insights.

In manufacturing and supply chain management, Data Science optimizes processes by predicting equipment failures, improving demand forecasting, and enhancing inventory management. It contributes to operational efficiency, cost reduction, and streamlined supply chain operations.

In e-commerce, Data Science analyzes customer behavior and transaction data to provide personalized recommendations. Machine learning algorithms power recommendation systems, enhancing user experiences, boosting engagement, and driving increased sales and customer satisfaction.

Participating in Data Science Internships is significant for gaining practical exposure to real-world projects. It allows individuals to apply theoretical knowledge, develop hands-on skills, and understand industry dynamics. Internships also enhance resumes, facilitate networking, and often lead to full-time employment opportunities.

While a bachelor's degree in a related field is common, advanced degrees such as a master's or Ph.D. are advantageous. Relevant skills, experience, and a solid foundation in mathematics and programming are crucial.

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FAQ’S OF DATA SCIENCE TRAINING IN AMMAN

Delving into the data science education landscape, DataMites stands out by offering a spectrum of certifications. The flagship Certified Data Scientist course provides in-depth knowledge, while specialized tracks like Data Science for Managers and Data Science Associate cater to diverse skill sets. 

The Diploma in Data Science offers a comprehensive curriculum, and specific courses in Statistics, Python, and various business domains such as Marketing, Operations, Finance, and HR provide a holistic learning approach.

Renowned globally, the DataMites Certified Data Scientist Course in Amman is a leading, all-encompassing program in Data Science and Machine Learning. Continuously updated to meet industry demands, this course is meticulously designed for structured and effective learning. With a focus on job readiness, it equips participants with the skills required to excel in the competitive realm of data science.

Certainly, before committing to the data science training fee in Amman, participants have the opportunity to attend a demo class with DataMites, allowing them to assess the course structure and content.

Newcomers in Amman can embark on their data science journey with accessible beginner-level training. The Certified Data Scientist course lays a robust foundation, while Data Science in Foundation introduces fundamental concepts. The Diploma in Data Science offers a comprehensive beginner-friendly curriculum. These courses from DataMites provide individuals with the essential knowledge needed to navigate and excel in the field of data science.

Yes, DataMites guarantees live projects as a component of their Data Scientist Course in Amman, encompassing more than 10 capstone projects and an impactful client/live project.

Absolutely, DataMites caters to the unique needs of working professionals, providing specialized data science courses such as Statistics, Python, and Certified Data Scientist Operations. Tailored offerings in Data Science with R Programming, and Certified Data Scientist courses for Marketing, HR, and Finance focus on targeted skill development.

DataMites' data scientist courses in Amman span from 1 to 8 months, with the duration determined by the course level.

Opting for online data science training in Amman with DataMites allows participants to learn conveniently from any location, breaking free from geographical limitations. The interactive online platform promotes engagement through discussions, forums, and collaborative activities, enriching the data science training experience.

The fee structure for DataMites' data science course fee in Amman ranges from JOD 375 to JOD 937, providing participants with flexibility in choosing a plan that suits their learning needs and budget.

DataMites selects trainers based on their elite status, with faculty members who have real-time experience from leading companies and renowned institutes like IIMs conducting the data science training sessions.

Absolutely, participants are required to bring a valid photo identification proof, such as a national ID card or driver's license, to collect their participation certificate and, if needed, to schedule the certification exam in the data science training sessions.

If a participant misses a data science training session in Amman, DataMites provides recorded sessions for review, allowing individuals to catch up on the content. Additionally, participants can schedule one-on-one sessions with trainers to discuss any questions or uncertainties related to the missed session, ensuring a thorough understanding of the material.

Yes, DataMites offers Data Science Courses with internships in Amman, providing practical exposure through internships with AI companies.

Specifically designed for managers and leaders, "Data Science for Managers" at DataMites is the perfect course to integrate data science into decision-making processes.

Yes, participants completing the data science course training in Amman with DataMites are awarded a certification, acknowledging their accomplishment and expertise in the realm of data science.

Certainly, in Amman, DataMites provides help sessions, allowing participants to seek assistance and gain a deeper understanding of specific data science topics during their training.

DataMites grants IABAC Certification upon completion of Data Science Training in Amman, acknowledging participants' proficiency in the field.

DataMites' Flexi-Pass in Amman empowers participants to customize their data science training schedule, offering flexibility to align with individual commitments. This ensures a personalized and convenient learning experience.

In Amman, DataMites' career mentoring sessions are structured to provide personalized guidance, helping participants navigate the data science job market successfully through expert insights and strategic advice.

At DataMites, the data science course training in Amman is conducted through online data science training in Amman and self-paced training methods, ensuring adaptability and personalized learning experiences.

There are no prerequisites for Certified Data Scientist Training in Amman, making it suitable for beginners and intermediate learners in data science.

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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