Launch your career in Data Science. By mastering the skills and techniques covered in these courses, students will be better equipped to handle the challenges of real-world data analysis.
What you'll learn:
- Define techniques and methods for collecting data from various sources including files, web, databases, etc.
- Identify statistical analysis and visualization techniques that can be used to gain insights into the data.
- Calculate and apply techniques for data preprocessing such as dealing with missing values, outliers, sampling, normalization, and discretization.
The "Classification Analysis" course provides you with a comprehensive understanding of one of the fundamental supervised learning methods, classification. You will explore various classifiers, including KNN, decision tree, support vector machine, naive bayes, and logistic regression, and learn how to evaluate their performance. Through tutorials and engaging case studies, [...]
The "Data Wrangling Project" course provides students with an opportunity to apply the knowledge gained throughout the specialization in a real-life data wrangling project of their interest. Participants will follow the data wrangling pipeline step by step, from identifying data sources to processing and integrating data, to achieve a [...]
The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present [...]
Data wrangling is a crucial step in the data analysis process, as it involves the transformation and preparation of raw data into a suitable format for analysis. The "Fundamental Tools for Data Wrangling" course is designed to provide participants with essential skills and knowledge to effectively manipulate, clean, and [...]
The "Data Processing and Manipulation" course provides students with a comprehensive understanding of various data processing and manipulation concepts and tools. Participants will learn how to handle missing values, detect outliers, perform sampling and dimension reduction, apply scaling and discretization techniques, and explore data cube and pivot table operations. [...]
The "Data Collection and Integration" course provides students with comprehensive techniques for gathering data from diverse sources, including files, relational databases, web pages, and APIs. Participants will gain practical experience in collecting and integrating data for further processing and analysis. The course emphasizes the utilization of appropriate tools and [...]