Data Analysis & Foundations
Skills You Will Gain
After completing this course, students will gain:
• Data analysis and data interpretation skills
• Python programming for data science
• Experience with data visualization tools
• Knowledge of machine learning fundamentals
• Ability to work with structured datasets
• Practical data science project experience
Real-World Applications of Data Science
Data Science is widely used in industries such as:
• Business analytics and market research
• Healthcare and medical data analysis
• Finance and risk prediction
• E-commerce recommendation systems
• Artificial Intelligence and Machine Learning
Course Outcome
By the end of this course, learners will have a strong foundation in data science and the practical skills required to begin working with real-world data and analytics tools.
Who This Course Is For
This course is ideal for:
• Beginners interested in Data Science
• Students pursuing careers in data analytics
• Professionals looking to transition into data science roles
• Developers wanting to learn data analysis skills
• Anyone interested in working with data and analytics
Archive
Working hours
| Monday | 9:30 am - 6.00 pm |
| Tuesday | 9:30 am - 6.00 pm |
| Wednesday | 9:30 am - 6.00 pm |
| Thursday | 9:30 am - 6.00 pm |
| Friday | 9:30 am - 5.00 pm |
| Saturday | Closed |
| Sunday | Closed |
- Description
- Curriculum
- Reviews
The IBM Data Science Professional Certificate course at AzraasTech is designed to provide learners with the essential skills required to start a career in data science. This program introduces students to the core concepts of data analysis, data visualization, machine learning, and data-driven decision making using industry-standard tools.
Data Science is one of the fastest-growing fields in technology. Organizations across industries rely on data scientists to analyze large datasets, uncover patterns, and generate insights that help businesses make informed decisions.
This course provides hands-on experience with tools such as Python, SQL, Jupyter Notebooks, and data visualization libraries, enabling learners to work with real-world datasets and build practical data science projects.