Get Ahead in Your Data Science Career with this Algorithmic Toolbox Course by Coursera
08 June 2023
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Course Overview
This Algorithmic toolbox course covers algorithmic techniques' fundamentals and solutions to real-world applications' computational problems like Divide and conquer, Greedy algorithms, and Dynamic Programming. Learn sorting data and searing; breaking large problems down into smaller pieces and solving them recursively, and about the dynamic programming used in genomic studies in this program.
The instructors Neil Rhodes, Michael Levin, Alexander S Kulikov are well versed with the topic and present it in an interesting format with ample examples of real-world problems solved using algorithms.
"This course is a good option if you are looking to learn the fundamentals of algorithmic techniques. I use the Greedy strategies taught every day as my job requires me to write scripts for back testing strategies."
- Gaurav Maddesia
Course Structure
It is an intermediate-level course being taught completely online. It offers an opportunity for hands-on training and participation in instructor-moderated discussions.
The course imparts:
- A clear understanding of the inner mechanisms of various algorithms, such as divide and conquer, greed and dynamic.
- Ability to understand the nature of the problem and the type of algorithm that should be implemented to get optimum performance.
- Limits and capabilities of algorithms used in various applications
The course was well-structured, and its topics became complex with each subsequent module. We started with Greedy, then we moved on to Divide and Conquer and later to Dynamic Programming, which, though hard concepts, were made easy to understand by the instructors.
Insider Tips
To get the best out of this course, I have included some important tips that you might find useful.
Make Notes
Try to make proper notes for each topic so that you get a better understanding of the content being covered in the course.
Prerequisites
To be successful in this course, one needs to have a strong grasp of the basic concepts of algorithm design. You should know at least 1 programming language before enrolling for this course. Taking this course: Python Fundamentals can help you with this.
Assessments
Try to solve assessments on your own. Assessments were nicely presented with questions of varying difficulty levels. At the end of each module, we were given a set of problems to solve and were evaluated based on the quality of our code.
Final Take
I am a part-time Python Developer Intern at a Bangalore-based firm, AlgoFno. My responsibilities include writing scripts for backtesting various strategies. This requires efficient coding. The Greedy strategies, taught in this course helps me daily in writing the scripts.
I opted for this course as it had a good rating and covered every topic I wished to learn.
Taking this course also helped me get a job offer. I was able to clear the interview tests designed to gauge my command of algorithms because of the training received in this program.
Key Takeaways
Gain a clear understanding of inner mechanisms of various algorithms such as Divide and Conquer, Greedy and Dynamic
Understand the nature of problem and type of algorithm that should be implemented to get optimum performance
Learn about limits and capabilities of algorithms used in various applications
Learn about solutions to real-world applications' computational problems
Develop a strong foundation in algorithmic techniques
Course Instructors
Gaurav Maddesia
Software developer
Software developer with experience in MERN stack, automation, and scripting
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