In this course, you will gain a solid understanding of the principles of machine learning, data analytics, and predictive modelling. The course focuses on practical hands-on experience using Python (NumPy, Pandas, Matplotlib and Scikit-learn), R (ggplot2, tidyverse) and My SQL to give you the tools you need to clean, analyse, and model real-world datasets.
The Certified Data Scientist program is designed to be accessible and beginner-friendly.
No prior experience is required, making it suitable for learners from diverse academic and professional backgrounds.
Ideal for both beginners and working professionals who wish to develop practical skills in data science and machine learning.
Basic computer literacy and logical thinking are recommended to ensure smooth learning.
A genuine interest in data-driven technologies and problem-solving will help participants get the most out of this program.
Certified Data Scientist (CDS – DS2050) by IABAC
Cost : $215 USD (official exam fee, as per IABAC® pricing)
Exam Format : Online proctored exam featuring multiple-choice questions and a case study/project evaluation, with a duration of 120 minutes.
Free Application Support : When you register through us, our team will guide you through the entire exam application process at no additional cost.
Access to Expert Resources : Get study guides, practice questions, mock exams, and access to a professional community of data science learners and experts.
Upon completion, participants will be able to:
Understand Python syntax and semantics for various programming paradigms.
Develop applications, scripts, and tools using Python.
Utilize Python’s extensive libraries and frameworks for data analysis, web development, and more.
Apply best practices for code quality, testing, and version control.
Solve complex problems with efficient, readable, and reusable code.
Prepare for further advanced studies or professional certifications in Python.
Our Certified Data Scientist program is built to provide a well-rounded, industry-relevant learning experience that helps you master both the fundamentals and practical applications of machine learning.Beginner-Friendly & Progressive Curriculum – Structured modules that guide you from Python basics to advanced machine learning applications.
Hands-On Training – Practical exercises and coding labs with NumPy, Pandas, and Scikit-learn on real-world datasets.
Capstone Project – End-to-end project that demonstrates your ability to analyse data, build models, and generate business insights.
Interactive Learning – Quizzes, assignments, and coding challenges to strengthen your understanding.
Industry Case Studies – Exposure to real-world applications in finance, healthcare, retail, and technology.
Expert Guidance – Learn directly from trainers with proven expertise in data science and AI.
Flexible Online Learning – Attend live sessions or study at your own pace with lifetime access to course materials.
LinkedIn Shareable Certificate – Earn a professional certificate to showcase your achievement and boost your career profile.
The training is offered as an exclusive one-to-one program and can include up to three participants. For larger groups, kindly submit your request through the Corporate Training Enquiry button, and our team will get in touch with you shortly.
Python Basics: Syntax, data types, control structures, functions, and modules.
Data Handling: Working with files, JSON, and databases.
Web Development: Introduction to frameworks like Flask and Django.
Data Analysis and Visualization: Using libraries such as Pandas, NumPy, and Matplotlib.
Object-Oriented Programming (OOP) and Design Patterns in Python.
Automation and Scripting: Simplifying tasks and processes with Python scripts.
Advanced Features: Decorators, generators, and context managers.
Introduction to Machine Learning with Python: Basics of scikit-learn and TensorFlow.
To enroll, simply visit the course section above and click on “Enroll Now” (this will redirect you to checkout). Once your enrollment is confirmed, you will automatically receive LMS access and be contacted by our administrators for next steps. You may also request a free demo session before finalizing your registration. For assistance, you can contact our sales team via WhatsApp or call at +974 7079 7089. Optionally, you may email us at info@teamacademy.net for more details.
No prior experience in machine learning or data science is required. This program is designed for both beginners and professionals. As long as you have basic computer literacy and a genuine interest in the field, you are welcome to join. Our instructors guide you step by step, making it easy to learn even if you are new to coding or data analysis.
Upon successfully completing the training and final project, you will be awarded a LinkedIn Shareable Certificate from Team Academy. This certificate validates your skills in data analysis and machine learning using NumPy, Pandas, and Scikit-learn, and can be added to your LinkedIn profile to enhance your career visibility.
Yes, we offer customized training solutions for corporates, institutions, and teams who wish to upskill their employees in data science and machine learning. Group packages and corporate discounts are available. For tailored training plans, you can directly contact us at info@teamacademy.net.
You can reach out to our sales and support team via WhatsApp or call at +974 7079 7089 for quick assistance. Alternatively, you can email us at info@teamacademy.net. Our team will provide complete guidance on enrollment, demo sessions, payment options, and course schedules.
This program is built around Python, the leading language in data science and AI. You will gain hands-on experience with essential libraries such as NumPy for numerical computations, Pandas for data manipulation, Matplotlib and Seaborn for visualization, and Scikit-learn for building and evaluating machine learning models.
Yes. The curriculum includes a wide range of machine learning methods, starting from supervised learning techniques like regression and classification, to unsupervised learning approaches such as clustering and dimensionality reduction. This ensures you build a complete understanding of different ML applications.
The course is highly practical and project-driven. Each module comes with coding exercises, real-world datasets, and mini-projects, giving you the opportunity to apply what you learn immediately. A capstone project at the end allows you to showcase your ability to solve real data problems end-to-end.
Yes. Data preparation is a crucial step in data science, and you will master techniques like handling missing values, removing outliers, feature engineering, and exploratory data analysis (EDA). These skills will enable you to work confidently with raw, messy datasets.
You will learn how to use evaluation metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. Additionally, you’ll practice advanced techniques like cross-validation, hyperparameter tuning, and feature selection, ensuring your models deliver reliable results in real-world scenarios.