This course is designed for those interested to learn the basics of the business applications of data science, how to develop an effective resume and cover letter, how to prepare for coding interviews, and how to present projects.
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Who this course is for:
- Business owners
- Data scientists
- Data analysts
What you’ll learn:Â
- The different data science titles and roles
- Resume and cover letter writing tips to help you sell yourself more effectively
- Sites that help in developing effective resumes and cover letters
- Mock interview questions about Python, R, Machine learning
- Python coding challenges
- How to present data science projects
- Software that you can use in data analysis
Requirements:Â
- No prior knowledge is required to take this course
The most important step to landing a job is being prepared. You’ll feel more in control and confident. In this course, you will learn how to prepare as a data scientist.
Our Promise to You
By the end of this course, you will have learned how to prepare for your job application as a data scientist.
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Course Curriculum
| Section 1 - Data Science Career Overview | |||
| Data Science Roles | 00:00:00 | ||
| Data Science Resumes | 00:00:00 | ||
| Data Science Cover Letters | 00:00:00 | ||
| Section 2 - Interviews | |||
| Python Interview Questions Part 1 | 00:00:00 | ||
| Python Interview Questions Part 2 | 00:00:00 | ||
| R Interview Questions | 00:00:00 | ||
| Machine Learning – Statistics Interview Questions | 00:00:00 | ||
| Python Coding Challenges | 00:00:00 | ||
| Section 3 - Projects | |||
| Web Scraping Project Part 1 | 00:00:00 | ||
| Web Scraping Project Part 2 | 00:00:00 | ||
| Finding Datasets | 00:00:00 | ||
| Education Project Part 1 | 00:00:00 | ||
| Education Project Part 2 | 00:00:00 | ||
| Section 4 - Additional Data Analysis Software | |||
| Github | 00:00:00 | ||
| SQL | 00:00:00 | ||
| Tableau | 00:00:00 | ||
| Excel Or Google Sheets Part 1 | 00:00:00 | ||
| Excel Or Google Sheets Part 2 | 00:00:00 | ||
| Outro | 00:00:00 | ||
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