DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE LEAD MENTORS

DATA SCIENCE COURSE FEE IN TUNIS, TUNISIA

Live Virtual

Instructor Led Live Online

TND 5,380
TND 3,453

  • 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

TND 3,230
TND 2,100

  • 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

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UPCOMING DATA SCIENCE ONLINE CLASSES IN TUNIS

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 TUNIS

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 TUNIS

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN TUNIS

Step into the realm of data science, a global force reshaping the future. The data science platform market, surging from US$ 8.9 Billion in 2022 to a projected US$ 48.5 Billion by 2028, indicates substantial growth (CAGR 32.87%, 2023-2028, IMARC Group). In Tunisia, a hub of technological progress, the data science industry presents distinctive opportunities and challenges. Tunis, the capital, plays a pivotal role in this evolving landscape. Witness the impactful convergence of innovation and analytics, offering promising career pathways in the dynamic field of data science.

In Tunis, the bustling capital of Tunisia, DataMites emerges as the premier institute for data science training in Tunis. Our globally recognized Certified Data Scientist Course in Tunis caters to beginners and intermediate learners, providing a robust foundation in data science principles. Unravel the intricacies of the world's most popular, comprehensive, and job-oriented data science program. Elevate your credentials with IABAC Certification, solidifying your expertise in the dynamic field of data science.

DataMites: Tailored Data Science Learning in Tunis

In the vibrant city of Tunis, DataMites offers a structured and impactful data science training program organized into three pivotal phases:

Phase 1: Pre-Course Self-Study

Initiate your educational journey with high-quality videos, employing an easy learning approach to lay the foundation for your data science expertise.

Phase 2: Live Training

Engage with a comprehensive syllabus, participating in hands-on projects under the guidance of expert trainers and mentors. Acquire a practical understanding of data science concepts through interactive live sessions.

Phase 3: 4-Month Project Mentoring

Conclude your training with a 4-month project phase, featuring mentorship, internship opportunities, 20 capstone projects, involvement in one client/live project, and an experience certificate to reinforce your practical skills. DataMites ensures a tailored and effective learning experience in the dynamic field of data science in Tunis.

Ashok Veda and Expert Faculty

Benefit from the leadership of Ashok Veda, a seasoned professional with over 19 years of experience in data science and analytics. As the Founder & CEO at Rubixe™, his expertise ensures top-tier education in the dynamic realms of data science and AI.

Course Curriculum - 8-Month & 700+ Learning Hrs.

Immerse yourself in an extensive 8-month program with 700+ learning hours, providing a comprehensive understanding of data science principles and techniques.

Global Certification - IABAC® & NASSCOM® Certification

Elevate your professional standing with globally recognized data science certifications, including IABAC®, endorsing your proficiency in data science.

Flexible Learning - Experience the flexibility of online data science courses accommodating diverse learning preferences and schedules.

Projects with Real-World Data and Internship Opportunity

Apply your knowledge through 20 capstone projects and one client project, actively engaging with real-world data. Seize internship opportunities to enhance your practical skills, paving the way for a successful career.

Career Guidance and Job References

Navigate your career path with end-to-end job support, personalized resume and data science interview preparation, and stay informed with job updates and valuable connections.

DataMites Exclusive Learning Community

Join an exclusive learning community, fostering collaboration and networking among DataMites students and professionals, creating a supportive and interactive environment.

Affordable Pricing and Scholarships - Affordable Pricing

Access quality education at an affordable cost with DataMites' pricing for Data Science courses in Tunis, ranging from TND 1618 to TND 4045. Explore scholarship opportunities to further support your educational journey, ensuring affordability without compromising excellence at DataMites.

Data Scientists In Tunis, enjoy lucrative career prospects, with an average monthly salary of TND 3,300, as reported by Glassdoor. This highly competitive compensation underlines the recognition and value placed on data science expertise in the job market. Data Scientists are sought after for their ability to decipher complex datasets, making them an integral and highly compensated part of the workforce in Tunis.

DataMites emerges as the unrivaled choice for data science training course in Tunis. Led by Ashok Veda, our courses offer unparalleled insights, endorsed by certifications such as IABAC®. With a flexible learning approach, real-world projects, and internship opportunities, DataMites ensures a seamless transition into the dynamic field of data science. Beyond data science, explore our diverse courses including Artificial Intelligence, Python, Data Analytics, Machine Learning, Data Engineering, Tableau, and more. Choose DataMites as your gateway to comprehensive education, paving the way for a successful and rewarding career in the ever-evolving tech landscape.

ABOUT DATAMITES DATA SCIENCE COURSE IN TUNIS

Data Science involves extracting insights from data using scientific methods, algorithms, and systems. It integrates statistical analysis, programming, and domain expertise to uncover patterns, trends, and valuable information for informed decision-making.

Real-world applications benefiting from Data Science include finance for risk analysis, healthcare for predictive modeling, marketing for customer segmentation, and technology for algorithm development. It revolutionizes processes and enhances decision-making across diverse industries.

Beginner-friendly data science projects include predicting housing prices, sentiment analysis on social media, or creating a basic recommendation system. These hands-on projects provide valuable experience in data manipulation, visualization, and basic machine learning concepts.

Courses for Data Science Certification are open to individuals with diverse backgrounds. Students, working professionals, or anyone passionate about data analysis can enroll to gain expertise in statistical analysis, programming, and machine learning.

While a degree in data science, computer science, or related fields is beneficial, practical skills and experience are crucial. Successful data scientists often hold degrees in mathematics, statistics, engineering, or have interdisciplinary backgrounds.

Essential tools for data scientists include programming languages (Python, R), statistical software (SAS, SPSS), and frameworks (TensorFlow, scikit-learn). Visualization tools like Tableau and programming environments like Jupyter are commonly used for data analysis.

Commonly utilized programming languages in data science are Python and R. Python's versatility and extensive libraries make it widely adopted, while R is preferred for statistical analysis and data visualization.

Indispensable skills for aspiring Data Scientists include proficiency in programming languages, statistical analysis, machine learning, data wrangling, and effective communication. Critical thinking, problem-solving, and domain-specific knowledge are crucial for success in this multifaceted field.

In Tunis, a Data Scientist typically starts as an entry-level analyst, advancing to Senior Data Scientist or Analytics Manager. Further progression may involve specialization in machine learning or transitioning to leadership roles within the data science domain.

The Data Science process involves iterative steps, including data collection, cleaning, exploration, modeling, validation, and interpretation. This cyclical approach allows for the extraction of insights, pattern discovery, and informed decision-making.

Data Science is applied practically in Tunis across various industries. In finance, it aids in risk analysis; healthcare utilizes predictive modeling; marketing employs customer segmentation, and technology develops algorithms. These applications optimize processes and inform decision-making.

In e-commerce, data science analyzes user behavior and historical data to power recommendation systems. These systems enhance customer experience by providing personalized product suggestions, driving engagement, and increasing sales.

The Certified Data Scientist Course is Tunis's top-rated program for aspiring data professionals. Covering programming, machine learning, and data analysis, it ensures participants acquire the skills essential for a successful career in data science, making it highly recommended in Tunis's educational landscape.

Yes, internships in data science hold significant value in Tunisia. They provide practical experience, exposure to real-world projects, and networking opportunities, enhancing employability in the competitive job market. Practical skills gained during internships are highly sought after by employers in Tunis.

Data science professionals in Tunis, experience promising career opportunities, boasting an average monthly salary of TND 3,300, according to Glassdoor. This reflects the favorable conditions in the field, indicating that data science is a financially rewarding profession in Tunis.

Yes, individuals with no prior experience can pursue data science training and secure jobs in Tunis. Building a robust skill set, completing projects, and networking can open doors in Tunisia's growing data science job market.

Data science optimizes manufacturing and supply chain operations by predicting demand, optimizing inventory, and improving logistics. Predictive maintenance and quality control further streamline processes, reducing inefficiencies and improving overall efficiency.

To kickstart a data science career in Tunis, one should acquire relevant skills through online courses, build a portfolio of projects, and engage with local data science communities. Networking with professionals, considering internships, and staying updated on industry trends are crucial steps.

Yes, transitioning from a non-coding background to data science is feasible. Learning programming languages, gaining statistical and machine learning skills, and building a strong foundation through online courses and projects can facilitate a successful transition.

Industries actively seeking to hire Data Scientists in Tunis include finance for risk analysis, healthcare for predictive modeling, technology for algorithm development, and e-commerce for customer analytics. Emerging sectors like smart cities and renewable energy also demonstrate a growing demand for data science expertise.

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FAQ’S OF DATA SCIENCE TRAINING IN TUNIS

Yes, participants in the Data Scientist Course offered by DataMites in Tunis will have the opportunity to work on live projects, including 10+ capstone projects and a client/live project for practical, hands-on learning experiences.

DataMites in Tunis stands out with its diverse offerings in data science certifications, covering the Certified Data Scientist, Data Science for Managers, Data Science Associate, Diploma in Data Science, Statistics for Data Science, Python for Data Science, and specialized courses in Marketing, Operations, Finance, HR, and R. This range ensures that professionals at different levels and from various industries can find suitable programs to enhance their expertise in data science.

For those new to the field in Tunis, DataMites offers beginner-level data science training, including Certified Data Scientist, Data Science in Foundation, and Diploma in Data Science. These accessible courses equip beginners with essential skills and knowledge, providing a solid foundation for a career in data science.

Widely acclaimed, the DataMites Certified Data Scientist Course in Tunis is globally recognized as a top-tier, job-centric program in Data Science and Machine Learning. Its ongoing updates, attuned to industry needs, establish a structured learning process, promoting effective and efficient skill development.

DataMites addresses the learning needs of working professionals in Tunis with specialized data science courses. The offerings, such as Statistics for Data Science, Data Science with R Programming, Python for Data Science, Data Science Associate, and Certified Data Scientist courses in Operations, Marketing, HR, and Finance, are tailored to provide targeted knowledge and skills for professionals seeking to augment their expertise in specific areas of data science.

DataMites data scientist courses in Tunis offer durations from 1 to 8 months, allowing learners to choose based on their preferred depth of study and expertise level. This flexibility ensures a tailored learning experience for individuals at various stages of their data science journey.

The Certified Data Scientist Training in Tunis is open to beginners and intermediate learners with no prerequisites, ensuring accessibility for individuals starting their journey in the field of data science.

DataMites' data science training in Tunis present a strategically organized fee structure, providing options from TND 1618 to TND 4045. This ensures accessibility for a variety of budgets and learning needs among aspiring data science professionals.

Certainly, DataMites offers Data Science Courses with internship in Tunis, allowing participants to engage with AI companies for practical learning experiences.

At DataMites, trainers are carefully selected based on their expertise and real-world experience. The data science training sessions are led by elite mentors and faculty members with hands-on exposure from leading companies and premier institutes like IIMs, guaranteeing a high-quality and industry-relevant learning experience.

When attending data science training sessions, participants must carry a valid photo identification proof, such as a national ID card or driver's license. This is imperative for obtaining a participation certificate and arranging any relevant certification exams.

Participants who miss a data science training session in Tunis at DataMites can access recorded sessions, receive study materials, and schedule makeup sessions.

Experience a complimentary demo class for our data science training in Tunis. This preview is designed to showcase our teaching approach, enabling you to evaluate content and teaching style before making any decisions about the training fee.

DataMites' "Data Science for Managers" course is designed for managers or leaders looking to integrate data science into decision-making, offering a strategic perspective on leveraging data for better decision outcomes.

Certainly, participants in Tunis can choose to attend help sessions, offering a valuable opportunity to improve their understanding of specific data science topics. These sessions are interactive, allowing participants to engage in discussions, seek clarification, and reinforce their knowledge. The availability of help sessions demonstrates a commitment to providing tailored support, ensuring participants in Tunis can navigate data science topics with confidence.

DataMites awards IABAC certifications upon successful completion of Data Science Training in Tunis, ensuring participants receive industry-recognized validation for their acquired skills.

Representing a paradigm shift in data science education, the Flexi-Pass offers a revolutionary method, giving learners the autonomy to craft their educational trajectory. This framework empowers students to personalize their curriculum, pick specific modules, and regulate their learning pace. Catering to various schedules and preferences, Flexi-Pass promotes a customized and proficient understanding of data science concepts.

Career mentoring sessions in the training follow a carefully designed structure. Participants experience one-on-one interactions with experienced mentors, addressing key elements like setting career goals, refining skills, and navigating the data science job landscape. The structured format guarantees that participants receive tailored advice and support, creating a supportive atmosphere for making informed decisions about their professional journeys.

Enrolling in online data science training in Tunis with DataMites provides the convenience of learning from any location, overcoming geographical limitations. The interactive online platform fosters engagement through discussions, forums, and collaborative activities, contributing to an enriched data science training experience.

DataMites facilitates data science course training through online data science training in Tunis and self-paced methods, providing participants with flexibility and control over their learning schedules.

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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