Data Science Projects 101 Build your Data Science Portfolio

Data Science projects for beginners | Data Science Portfolio Projects | Beginner Data Science Projects
What you'll learn:
Students will gain practical experience by completing a series of guided data science projects from start to finish.
Students will create a portfolio showcasing their acquired skills and demonstrating their abilities in real world projects.
Students will enhance their portfolios by including high-demand domain projects such as computer vision, natural language processing and time series analysis.
Participants will stay updated with the latest trends and advancements in the field of data science by exploring relevant industry case studies.
Students will receive personalized guidance and feedback on their projects to further refine their skills and career trajectory.
Requirements:
Basic Python Knowledge: In order for you to take this course, you must understand the python programming language and should be able to write simple code in Python.
Basic Data Science Knowledge: The student must be aware of the basic data science concepts data cleaning, exploratory data analysis, training a model etc.
Curiosity and Eagerness to Learn: Most importantly, students should come with a curiosity and eagerness to learn about data science concepts and apply them in practical projects. The course is designed to accommodate beginners and guide them through the learning process step-by-step.
Description:
Welcome to the Data Science Portfolio Builder course! This course is tailored for beginners who are eager to delve into the field of data science and build a solid portfolio of projects. This course covers everything that you need in order to prepare for your next interview. It consists of an end-to-end description of multiple Data Science projects, starting from explaining business aspects of running a Data Science solution, basic concepts of Data Science algorithms all the way up to training the model.Throughout the course, you will explore essential domains of data science, including time series analysis, natural language processing (NLP), computer vision, and graph neural networks (GNN). Each module is designed to provide you with a foundational understanding of these areas, progressing from basic concepts to practical applications.These are in-demand skills, something what the recruiters are looking for. By adding these projects, you would make your portfolio very versatile. I have included sensible projects in this course in terms of practicality, and not something which you might see on the internet, like a "Stock Price Predicting application". These projects are relevant in the industry and recruiters are looking to hire people who have a knowledge of them.By completing these projects, you will not only gain valuable experience but also build a portfolio that showcases your proficiency in data science to potential employers, even if your interview is next week!Whether you're a student, a career changer, or simply interested in expanding your skill set, this course will equip you with the necessary tools and knowledge to succeed in the dynamic field of data science.Enroll now and take the first step towards building your data science portfolio!
Who this course is for:
Students and recent graduates looking to build a portfolio for data science roles.
Professionals considering a career transition into data science.
Self-learners and hobbyists passionate about exploring data science concepts.
Those seeking hands-on experience in machine learning and data science.
Beginners wanting to understand fundamental data science concepts in a practical way.
Homepage
https://www.udemy.com/course/data-science-projects-101-build-your-data-science-portfolio/