Data Science - Python for Machine Learning
This online tutorial provides hands-on training for Machine Learning in Data Science using Python. Participants will gain experience working on data science projects and gain valuable skills. Enroll now to get started! ▼
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Course Feature
Cost:
Paid
Provider:
Eduonix
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
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Updated in [March 06th, 2023]
This course provides an introduction to Data Science and Machine Learning using Python. Participants will gain hands-on experience working on data science projects using Python. The course covers topics such as data manipulation, data visualization, predictive analytics, and machine learning algorithms. Participants will learn how to use Python to explore and analyze data, create visualizations, and build predictive models. Upon completion of the course, participants will have a better understanding of the fundamentals of data science and machine learning, and be able to apply these skills to their own projects.
[Applications]
The application of this course can be seen in various fields such as data analysis, data visualization, predictive analytics, and machine learning. It can be used to develop models and algorithms for data analysis and machine learning. It can also be used to create data-driven applications and services. Additionally, it can be used to develop data-driven decision-making systems and to create data-driven products and services. Finally, it can be used to develop data-driven solutions for businesses and organizations.
[Career Paths]
1. Data Scientist: Data Scientists use their knowledge of mathematics, statistics, and programming to analyze large datasets and uncover insights. They use their findings to develop predictive models and algorithms that can be used to make decisions and solve problems. Data Scientists are in high demand and the field is expected to continue to grow as more organizations rely on data-driven decision making.
2. Machine Learning Engineer: Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use their knowledge of programming, mathematics, and statistics to develop algorithms that can be used to solve complex problems. Machine Learning Engineers are in high demand and the field is expected to continue to grow as more organizations rely on machine learning to automate processes and make decisions.
3. Artificial Intelligence Engineer: Artificial Intelligence Engineers are responsible for designing, developing, and deploying AI-based systems. They use their knowledge of programming, mathematics, and statistics to develop algorithms that can be used to solve complex problems. Artificial Intelligence Engineers are in high demand and the field is expected to continue to grow as more organizations rely on AI-based systems to automate processes and make decisions.
4. Data Analyst: Data Analysts use their knowledge of mathematics, statistics, and programming to analyze large datasets and uncover insights. They use their findings to develop reports and visualizations that can be used to make decisions and solve problems. Data Analysts are in high demand and the field is expected to continue to grow as more organizations rely on data-driven decision making.
[Education Paths]
1. Bachelor of Science in Data Science: This degree program provides students with a comprehensive understanding of data science principles and techniques, including data mining, machine learning, and artificial intelligence. Students will learn how to use Python to analyze data, create predictive models, and develop data-driven solutions. Additionally, they will gain an understanding of the ethical implications of data science and the importance of data privacy.
2. Master of Science in Artificial Intelligence: This degree program focuses on the development of artificial intelligence systems and their applications in data science. Students will learn how to use Python to create intelligent systems, develop algorithms, and apply machine learning techniques. They will also gain an understanding of the ethical implications of artificial intelligence and the importance of data privacy.
3. Doctor of Philosophy in Data Science: This degree program provides students with an in-depth understanding of data science principles and techniques, including data mining, machine learning, and artificial intelligence. Students will learn how to use Python to analyze data, create predictive models, and develop data-driven solutions. Additionally, they will gain an understanding of the ethical implications of data science and the importance of data privacy.
4. Master of Science in Data Science and Machine Learning: This degree program focuses on the development of machine learning algorithms and their applications in data science. Students will learn how to use Python to create intelligent systems, develop algorithms, and apply machine learning techniques. They will also gain an understanding of the ethical implications of artificial intelligence and the importance of data privacy.
Pros & Cons
Good introduction to data science
Excellent content
Hands on learning opportunities
Limited hands on experience
Mostly lecture based learning
No practical application of concepts
Course Provider
Provider Eduonix's Stats at AZClass
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