Course Description

Data Science Courses
Data science courses typically cover a wide range of topics, including:
• Introduction to Data Science: This section will likely cover the core concepts of data science, including the data science life cycle, big data, business intelligence, and how data science interacts with machine learning and artificial intelligence (AI).
• Mathematics Fundamentals: Data science relies heavily on math. This section might introduce you to essential mathematical concepts like linear algebra, calculus, and probability & statistics, which are crucial for understanding data manipulation and analysis.
• Statistics for Data Science: Statistics plays a vital role in data exploration, analysis, and drawing meaningful conclusions. You might learn about descriptive statistics, hypothesis testing, inferential statistics, and common statistical tests used in data science.
• Programming for Data Science (likely Python): Python is a popular programming language for data science. The course might introduce you to Python basics, data structures, libraries like NumPy, Pandas, and Matplotlib used for data manipulation and visualization.
• Data Visualization with Tableau (possibly): Tableau is a data visualization tool. This section could cover how to create charts, graphs, and dashboards to effectively communicate insights from your data analysis.
• Advanced Statistics and Machine Learning: As you progress, the course might delve into more advanced topics like time series analysis, natural language processing (NLP), and various machine learning algorithms for tasks like classification and regression.
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Certification

Upon successful completion of this course and passing the final exam, you will receive a certificate of completion from GLOBEL GROUP to showcase your newfound skills.

Who This Course is for

Beginners with no prior experience in data science: This course is suitable for beginners who want to learn the basics of data science from scratch.
Professionals who want to switch their careers to data science: This course is suitable for professionals who want to gain the skills necessary to enter the field of data science.
University students studying data science-related disciplines: This course is suitable for university students studying data science-related disciplines, such as computer science, engineering, and statistics.