CORE Data Science and Machine Learning
This comprehensive course is designed with a clear objective: to equip you with the essential knowledge and skills required for your first day on the job in data science. We've distilled the curriculum to focus solely on what's relevant and practical, omitting any unnecessary fluff or advanced topics that aren't immediately applicable in real-world scenarios. Covering EVERY core topic and tool necessary for newcomers to data science—including Python, R, SQL, essential Math/Stats/Algorithms, Tableau, and Excel—our course delves deep into each subject.
Structured to align with three distinct job roles—Data Analyst, General Data Scientist, and Machine Learning Engineer—we guide you through the foundational principles and tools currently in use. Drawing from the instructor's extensive experience and the Data Science Road Map, a curated collection of top-tier resources, you'll embark on a journey that leaves no stone unturned.
In addition to mastering core skills, you'll explore essential technologies such as GitHub, Kaggle, cloud basics, web development, and docker. With over 200 videos, readings, and assignments, you'll emerge well-prepared to become an integral part of the data community.
This course is ideal for:
- Individuals unsure of where to begin their data science and machine learning journey
- Those dissatisfied with courses that fail to provide a comprehensive understanding of data science, leaving them with lingering questions
- Aspiring data science and machine learning professionals looking to kickstart their career
- Individuals seeking to enhance their existing skill set with the latest techniques and tools
What you'll gain:
- Proficiency in all essential core skills for Data Analysis, Data Science, and Machine Learning
- Insight into the foundational principles of data science and its significance in today's landscape
- Mastery of Python, R, SQL, Tableau, and MS Excel for data science applications
- Familiarity with a wide array of data science and machine learning libraries and resources
- Creation and hosting of a personal resume and portfolio of data science projects using GitHub Pages
- Knowledge of vital supporting skills such as Git/version control, Kaggle, Databases, Command Line tools, and more
- Ability to set up development environments from scratch in R and Python
- Understanding of important related technologies like cloud, docker, and web development
- Proficiency in deploying a machine-learning model using docker
CORE Data Science and Machine Learning
Any pre-loaded packaged materials or subscription-based products, including device-based training programs, and courses that include a device, may not be refunded. Digital products including DVDs may be returned for replacement if found defective
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