“Data Science Foundations” in this course, the essential concepts, and technologies used in the field of data science, including machine learning, statistical inference, and handling large amounts of data will be covered. The topic of data science is rapidly developing and there is a high demand for skilled and analytically inclined professionals. Data scientists are employed in a wide range of sectors and applications, and businesses of all sizes are hiring them. The course will begin by outlining the various responsibilities and abilities required for data science initiatives, as well as the complete data science process. The course will then delve into the fundamentals of data collection from various sources such as web APIs and page scraping. The system will show the student’s how to analyze and manipulate data using tools such as R, Python, the command line, and even spreadsheets. Additionally, the effective methods for data analysis will be discussed. Currently, udemy is offering the Data Science Foundations course for up to 44 % off i.e. INR 449 (INR 799).
Who can opt for this course?
- Those with an interest in data science
- Everyone who wants to become a data scientist
- Developers or programmers of software
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 03 Hours |
| Rating | 4.8/5 |
| Student Enrollment | 3,110 students |
| Instructor | Data Hawk https://www.linkedin.com/in/datahawk |
| Topics Covered |
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| Course Level | N.A |
| Total Student Reviews | 608 |
Learning Outcomes
- Using R, Python, and SQL to program
- Recognize the positions and professions in data science
- Data sourcing
- Mathematical and statistical data science
- Data science and artificial intelligence
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Welcome (02 minutes) | Welcome |
| Introduction | ||
| Course files | ||
| 2. | Data Science Intro (18 minutes) | A career in Data Science |
| Venn diagram and Pipeline | ||
| Roles and Team in Data Science | ||
| 3. | Fields of Study (10 minutes) | Big Data |
| Programming | ||
| Statistics | ||
| Ethics in Data Science | ||
| 4. | Data Sources (27 minutes) | Metrics |
| Existing Data Sets | ||
| APIs | ||
| Scraping | ||
| Creating Data | ||
| Data Exploration | ||
| 5. | Programming (21 minutes) | Spreadsheets |
| R: The Language of Data Science | ||
| Python | ||
| SQL | ||
| Web Formats | ||
| 6. | Mathematics (34 minutes) | Algebra |
| Systems of equations | ||
| Calculus | ||
| Big O | ||
| Bayes probability | ||
| 7. | Applied Statistics (21 minutes) | Hypothesis |
| Confidence | ||
| Problems and Validating | ||
| 8. | Machine Learning (27 minutes) | Decision Trees |
| Ensembles | ||
| k-nearest neighbors (kNN) | ||
| Naive Bayes classifiers | ||
| Artificial neural networks | ||
| 9. | Communicating (18 minutes) | Interpretability |
| Actionable insights | ||
| Visualization for presentation | ||
| Reproducible research | ||
| 10. | Conclusion (02 minutes) | Final words |
Resources Required
- Working knowledge of the R programming language
Featured Review
Alexander Desousa (5/5) : I m very happy I took this course I have learn a lot. I have to start applying it. the presentation is very good. it flows very well and it easy to understand.
Pros
- Nick Hayes (5/5) : I was particularly impressed by the clarity and professionalism of the presenter and the quality of the graphics throughout.
- Shanmugasundaram Muthuswamy (5/5) : It is really awesome that the course deals with all fundamentals required to become a well qualified data scientist.
- Brian Tremaine (5/5) : As an experienced engineer wanting to get into this field it was what I was looking for.
- Beat Sturzenegger (5/5) : Pleasant delivery with good use of media to relay the material.
Cons
- Sam R. (2/5) : Not all videos download on iPad. Same data science content can be found on youtube.
- Phani R. (2/5) : The author very knowledgeable. However course it too fast and short. Course assumes background in R and statistics
- Bhoomika R. (2/5) : very basic information which can be gathered over internet easily. For a paid course my expectation were different and definitely this is no where around it. 2 stars are only for the instructor as he is good with explanation but the content isnt up to the mark.
- Adam C. (2/5) : Too broad, even for an introductory course. I would’ve preferred an overview of how to do data science to an overview of the field.
About the Author
The instructor of this course is Data Hawk who is a Data Science. With a 4.8 Instructor Rating and 611 Reviews on Udemy, he/she offers 2 Courses and has taught 3,364 Students so far.
- DataHawk offers advice in data science and IT
- Their goal is to assist organizations in recognizing the value of their data
- With the use of high-volume data engineering, analysis, and predictive modeling, we are able to address complicated business challenges
- To assist the students in deciding how to use and use data science, they offer consultation services as well as custom development
- To provide the best solutions, our engineers, architects, and data scientists concentrate on your business concerns
Comparison Table
| Parameters | Data Science Foundations | Data Science 4 Newbs! Skills + Basic Web Experiment Analysis | Introduction to Machine Learning for Data Science |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 3 hours | 1.5 hours | 5.5 hours |
| Rating | 4.8 /5 | 4.3 /5 | 4.5 /5 |
| Student Enrollments | 3,110 | 2,204 | 58,209 |
| Instructors | Data Hawk | Larry Wai | David Valentine |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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