Data Science is an interdisciplinary field that consists of extraction, evaluation, interpretation, and presentation of data to gain insights and helps in decision-making. Data Interpretation, Data Collection, Data Cleaning and Preparation, Exploratory Data Analysis (EDA), Statistical Modelling and Machine Learning (ML), Data Visualisation, and Data-pushed Decision Making are a few of the tasks that fall beneath the umbrella of data science. To extract data from datasets, it uses of several techniques and tactics from statistics, mathematics, computers, and domain understanding. Some notable and famous courses on data science are below:
1. “Data Science Fundamentals”- by IBM on edX
An introduction to data science and its basic foundations is offered here. Data manipulation, data analysis, data visualisation, and ML models are included. It includes many practical tasks using Jupyter Notebooks and IBM Watson Studio.
2. “Introduction to Data Science in Python” – by the University of Michigan, USA through Coursera
Python, a programming language, is used in this course to introduce students to data science. It introduces several ML techniques like linear regression, clustering, and decision trees. It consists of hands-on programming assignments to understand principles. Utilising the pandas, matplotlib, and numpy libraries, it covers the fundamentals of data manipulation, analysis, and visualisation.
3. “Applied Data Science with Python” – by the University of Michigan through Coursera
This course focuses on applied data science techniques using Python. It also introduces text mining and social network analysis. It includes hands-on assignments and a final project where students apply the learned concepts to real-world datasets. It covers statistical inference, machine learning, data cleaning, data visualization, and exploratory data analysis.
4. “Data Science Specialization” – by Johns Hopkins University through Coursera
This specialization includes nine courses offering an elementary foundation in data science. Each of them has assignments and assessments to use the principles for real-time datasets. It covers R programming language, data visualization, data cleansing, statistical inference, ML, and real-time data science applications.
5. “Data Science and AI Foundations”- by IBM on Coursera
It provides a fundamental grasp of data science and AI concepts. It offers practical exercises and hands-on assignments using IBM Watson Studio to demonstrate how the ideas and concepts are applied in real-time applications. Data exploration, data visualisation, data cleaning, and AI and ML methods are among the topics it covers.
6. “Machine Learning” – by Stanford University on Coursera
The instructor of this course is Andrew Ng. It covers topics along with Support Vector Machines (SVM), linear regression, logistic regression, neural networks, and unsupervised ML models. The course provides a solid foundation in ML techniques and includes programming projects in MATLAB/Octave.
7. “Data Science and Machine Learning Bootcamp”- by Udemy, an online platform
This detailed bootcamp covers various data science and ML subjects. The course possesses practical assignments, coding examples, and practices from real-world situations. Data pre-processing, clustering, classification, EDA, regression, NLP, and deep learning are among the topics it covers.
8. “Introduction to Data Science”- by Microsoft on edX
In this course, the basic strategies and ideas of data science are studied. It covers data exploration, visualisation, model evaluation, and ML. It provides real-time situations using Microsoft Azure. It locations a high emphasis on facts, data, statistics, information, principles, generation, and ethics.
9. “Data Science and Big Data Analytics”- by Harvard University on edX
The techniques and approaches used in big data analytics and data science are offered in this course as a basic introduction. Real-time case studies and practical coding exercises using R and Python are available in the course. Data manipulation, EDA, visualisation, statistical modelling, machine learning, and big data analytics approaches are covered.
10. “Python for Data Science and Machine Learning”- by Udemy, an online platform
This course has the speciality of using Python, a programming language for ML and data science. Data pre-processing, visualisation, model evaluation, classification, clustering, NLP, and ML are among the topics it covers. It includes practical tasks, real-time case studies, and coding exercises to reinforce the applied principles and standards for real-world scenarios.
11. “Data Science and Machine Learning with Python”- by Udacity
This course provides a thorough introduction to Python-based data science and ML. Data cleaning, feature engineering, EDA, model assessment, and deployment of ML models are covered. Real-world projects, coding exercises, and interactive quizzes are a part in the course.
12. “Data Science for Business”- by the University of Colorado Boulder on Coursera
This course investigates how data science ideas can be applied in firms and businesses. Case studies and hands-on activities that use data science principles to real-time scenarios are an integral part of the course. Predictive modelling, data exploration, data visualisation, and data-driven strategy are among the topics it covers.
13. “Data Science and Analytics in Python”- by Columbia University on edX
This course focuses on data science and analytics using Python. The course additionally introduces NLP and network analysis. It includes coding examples, hands-on activities and real-world case studies using Python libraries. It covers visualization, data manipulation, statistical modelling, and ML.
14. “Data Science and Machine Learning using Python”- offered through edureka!
This course provides in-depth explanations of data science and ML concepts using Python. Pre-processing of data, EDA, regression, decision trees, classification, clustering, and NLP are covered. Assignments and practical exercises are included throughout the course to reinforce the topics.
15. “Advanced Data Science with IBM” – by IBM offered through edX
The focus of this advanced course is to offer cutting-edge data science methods and resources. For practical learning, the course includes hands-on exercises utilising Python and IBM Watson Studio. Data exploration, model evaluation, feature engineering, ensemble approaches, deep learning, and time series analysis are among the subjects it covers.
16. “Applied Data Science” – by IBM through Coursera
The practical use of data science tools, techniques, and technologies is the important and primary focus about this course. It includes ML algorithms, deep learning algorithms, data purification, visualisation, NLP, and EDA. The course comprises practical exercises and a final test in which you apply the ideas to sets of real data.
17. “Data Science for Executives” – by Columbia University on edX
This course is for data scientists, executives, and specialists who want to know the basic foundations of data science. It covers data analysis, statistical modelling, ML, NLP, deep learning algorithms, and data-driven decision-making. The course offers practical examples and case studies to illustrate data science in commercial enterprises.
18. “Data Science Ethics” – by University of Michigan on Coursera
Ethics in data science are covered in this course. It addresses issues including transparency, bias, data privacy, accountability, and responsibility. It has ethical theories and real-world scenarios to help executives, experts, data scientists, and data analysts contribute professionally, responsibly, and morally.
19. “Data Science and Machine Learning Bootcamp with R” – by Udemy, an online platform
The R programming language is discussed in this course as a thorough introduction to machine learning and data science. Deep learning algorithms, ML methods, NLP, statistical modelling, pre-processing of data, model evaluation, and EDA are all included in this process. Projects from the real world and exercises to put the theory into practice make up the course.
20. “Data Science and Machine Learning Bootcamp with Python” – through Udemy, an online platform
This course is a comprehensive bootcamp that covers data science and ML using Python. The course includes hands-on exercises, coding activities, real-world examples, and projects to reinforce the concepts taught. It covers data preprocessing, ML algorithms, deep learning, classification, EDA, regression, clustering, and NLP.
