Master in Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.
Data Science Courses revolves around the techniques of recording, looking at, and taking care of data to remove pieces of information and future estimates from coordinated and unstructured data.
I am delighted to welcome you into the course of Data Science. In this course, you will learn both the basics of conducting data science and how to perform data analysis in python.
Prerequisites:
This course is intended for learners who have a basic knowledge of programming in any language (Java, C, C++, Pascal, Fortran, JavaScript, PHP, python, etc.).
Course Overview:
First, and foremost, you’ll learn how to conduct data science by learning how to analyse data. That includes knowing how to import data, explore it, analyse it, learn from it, visualize it, and ultimately generate easily shareable reports. We’ll also introduce you to two powerful areas of data analysis: machine learning and natural language processing
To conduct data analysis, you’ll learn a collection of powerful, open source, tools including:
- Python
- Jupyter notebooks
- Pandas
- Numpy
- Matplotlib
- Scikit learn
- Nltk
- And many other tools
Learning Objectives
- Basic process of data science
- Python and Jupyter notebooks
- An applied understanding of how to manipulate and analyse uncurated datasets
- Basic statistical analysis and machine learning methods
- How to effectively visualize results
By the end of the course, you should be able to find a dataset, formulate a research question, use the tools and techniques of this course to explore the answer to that question and share your findings.
Discover your career as a Data Scientist!
