Statistics & Probability for Data Science & Machine Learning Overview
You will gain the fundamental understanding of probability and statistics needed for data science and machine learning from this course. You will learn a great deal about probability theory, investigate probability distributions, and delve into descriptive statistics. Regression analysis, hypothesis testing, and an introduction to sophisticated regression and machine learning algorithms are all covered in this course. By the end, you’ll be an expert at using statistical methods to analyse data and create strong machine learning models.
Learning Outcomes
- Use important statistical measures to describe and summarise data.
- Assess and examine data distributions’ characteristics.
- Utilise probability theory concepts to solve data science issues.
- Create and evaluate hypotheses with statistical techniques.
- For an understanding of the relationships between variables, do a linear regression analysis.
- Examine sophisticated regression methods and their uses.
- Learn about the most popular machine learning algorithms.
- Apply statistical techniques for the validation and assessment of machine learning models.
- Effectively communicate statistical conclusions and insights.
- Utilise machine learning and statistical methods to address practical data science issues.
Who Is This Course For
This course is intended for those who want to use probability and statistics in data analysis, including aspiring machine learning engineers and data scientists. This course offers a strong foundation for a successful career in data science, regardless of your prior experience in computer science, mathematics, or another quantitative field. Additionally, it is appropriate for professionals who work with data, such as analysts and researchers, and who wish to deepen their understanding of statistics.
Entry Requirements
- Age Requirement: Applicants must be aged 16 or above, allowing both young learners and adults to engage in this educational pursuit.
- Academic Background: There are no specific educational prerequisites, opening the door to individuals from diverse academic histories.
- Language Proficiency: A good command of the English language is essential for comprehension and engagement with the course materials.
- Numeracy Skills: Basic numeracy skills are required to effectively understand and work with course-related information.
Why Choose Us
- Affordable, engaging & high-quality e-learning study materials;
- Tutorial videos/materials from the industry-leading experts;
- Study in a user-friendly, advanced online learning platform;
- Efficient exam systems for the assessment and instant result;
- The UK & internationally recognised accredited
- Access to course content on mobile, tablet or desktop from anywhere, anytime;
- The benefit of career advancement opportunities;
- 24/7 student support via email.
Career Path
A solid background in probability and statistics paves the way to exciting career opportunities in data science and related fields. As a data scientist, you will use machine learning and statistical techniques to extract insights from large datasets. Alternatively, you could pursue a career as a statistician, planning and conducting statistical research to support decision-making. Completing this course equips you with the skills needed to embark on a rewarding career in this rapidly growing field.
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