#datascience #softwareengineering #tech How do I break into tech? How do I transition from my current field? Should I choose data science or software engineering? Do I need a degree? What is the best thing to study? What are the interviews like for each role? This video will answer all of these questions and more as part 2 of my Data Science VS Software Engineering series. Check out part 1 here: https://youtu.be/jGm0x_JbkD8 Timestamps Intro and overview - 0:00 Best degrees for data science and software engineering - 1:05 How to break in from an unrelated background / without a degree - 2:40 BEST strategy for breaking in (I've seen it work many times) - 3:05 My thoughts on software engineering / data science bootcamps - 4:31 Interview process comparison - 6:48 Final tips and takeaways - 10:01 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Google Data Analytics Professional Certificate: https://imp.i384100.net/rnjZj3 Mathematics for Machine Learning and Data Science Specialization https://imp.i384100.net/e4d9dz Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld Most responsive on YouTube comments, but you can also find me here: TikTok: damselindata IG: damselindata

#datascience #softwareengineering #techjobs If you need help deciding between data science and software engineering this in-depth career comparison is for you! We will go over what working in each job is like, including pros and cons, total compensation info ($$$) and the long-term job landscape for each one, including how they will both be affected by AI and other technological advancements! Timestamps Intro and overview - 0:00 Job comparison, similarities and differences, pros & cons - 1:42 Salary and total compensation comparison - 8:53 Job landscape and long-term job security - 10:30 Final tips to help you choose - 13:46 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld Most responsive on YouTube comments, but you can also find me here: TikTok: damselindata IG: damselindata

#dataliteracy #datascienceinterview #introtostatistics If you’re a citizen of today’s digital world, you need to watch this video. If you're trying to prep for your data science interview, you need to watch this video. Finally, if you’re interested in the number one most useful skill that data scientists have for every-day life, and you want to gain that skill in under 20 minutes, you need to watch this video! This video will teach you the basics of statistics in the context of consuming information and using data to draw valid conclusions. After watching, you will be able to interpret information and detect misinformation in your every-day life, just like a data scientist does :) Timestamps: Intro - 0:00 First thing to remember when consuming information - 1:51 Why statistics exists and why we can’t live without it - 3:55 How to apply statistics to properly interpret information: 6:16 Key Takeaways and Conclusion - 14:44 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld Most responsive on YouTube comments, but you can also find me here: TikTok: damselindata IG: damselindata

Ever wanted to hear about the career journey of a data scientist who thinks she’s qualified enough to make over-produced videos about it? No? Me neither. Here it is anyway. #datascience #datascientist #womenintech Timestamps: Intro - 0:00 Education - 1:55 How / when I got interested in data science - 4:15 Job 1 - 6:46 Job 2 - 8:23 Job 3 - 10:40 Job 4 - 12:10 Current Situation & Outro - 13:18 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld TikTok: damselindata IG: damselindata

The most helpful lessons I learned working as a data scientist and the surprising ways they translate to life lessons! Thank you to 365 Data Science for sponsoring today’s video! Go check out their brand new site and get a FREE month of full access to all of their data science courses taught by some amazing professionals! https://bit.ly/3BLGpuf Time Stamps: Intro - 0:00 Free month of data science learning ft 365 Data Science - 1:05 Data Science Lesson 1 - 1:56 Parallel Life Lesson 1 - 3:36 Data Science Lesson 2 -  6:53 Parallel Life Lesson 2 - 9:05 Data Science Lesson 3 - 11:29 Parallel Life Lesson 3 - 13:09 Conclusion - 15:03 #datascience #machinelearning #datascienceeducation

Will be covering who should take each course, my thoughts on the material, why it stands out and caveats / disclaimers. Hopefully this helps you choose the right beginner data science course for you! Timestamps Intro: 0:00 Why Coursera: 1:36 IBM Professional Data Science Certificate: 2:40 Python for Everybody: 7:39 Machine Learning by Stanford: 10:36 Final Thoughts: 13:47 🍍🍓🍋Juicy Juicy Links! 🍋🍓🍍 ** note: the links below are affiliate links, meaning I receive a small commission with every purchase MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 [Honourable Mention] Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld #datascience #machinelearning #python

If you've ever edited a spreadsheet and wondered what the equivalent Python code would be, this video is for you! Mito is a Jupyterlab extension that allows you to quickly and easily generate Pandas data analysis scripts using the Excel functions you already know. Shoutout to Mito for sponsoring this video! Mito Installation Instructions: https://docs.trymito.io/getting-started/installing-mito Learn more: https://trymito.io/DID Video Breakdown: Intro: 0:00-1:49 Installing Mito: 1:49-2:07 Importing data: 2:07-2:55 Merging data: 2:55-3:58 Pandas code being generated and why it's useful: 3:58-5:01 Filtering and sorting data: 5:01-6:13 Automatic summary stats and graphing: 6:13-6:37 Pivot tables: 6:37-7:07 Incorporating Excel functions: 7:07-7:56 Conclusion: 7:56-8:41 #dataanalysis #excel #python #datascience #jupyterlab #pandas

TIMESTAMPS: Intro: 0:00-0:43 5 things to learn: 0:43-2:02 Top Resources for self-study (videos, courses, books, websites & how to choose resources): 2:02-6:53 Discussion on degrees (do you need them to find a job, and how to choose what to study): 6:53-13:56 VIDEOS EXPLAINING CONCEPTS YOU NEED TO LEARN: Overview of learning data science theory, programming skills and hands-on experience: How to get a job in data science (1::11 - 5::15) -https://youtu.be/nSzLMenLFos Learning data science theory: Math you need to know for data science (esp from 11::05-13::33) - https://youtu.be/eJtHzkMy_1k Learning data science programming skills: What is a Data Scientist? (esp from 8::21-10::20) - https://youtu.be/E1pNOqyq8s8 Learning how to apply data science theory and programming skills in a project: How to build a machine learning model: https://youtu.be/KtKZVc0joYQ ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld ADDITIONAL RECOMMENDED RESOURCES FOR SELF-STUDY: Data Science from Scratch book: https://www.amazon.ca/Data-Science-Scratch-Principles-Python/dp/149190142X Data Science from Scratch Github repo: https://github.com/joelgrus/data-science-from-scratch Free e-book version of “Deep Learning” book - https://www.deeplearningbook.org/ Online Data Science Courses by Udemy: https://www.udemy.com/topic/data-science/ Andrew Ng’s Machine Learning Course by Stanford University / Coursera - https://click.linksynergy.com/deeplink?id=bZkOerDdGVE&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fmachine-learning Best site to get practical data science experience - https://www.kaggle.com/ Different Types of data scientists: https://youtu.be/E1pNOqyq8s8 (1::54-5::29) Blog Post: Breaking into data science with no degree - https://towardsdatascience.com/the-value-of-a-degree-for-aspiring-data-scientists-8c42a261e502 #datascience #machinelearning #datascienceeducation

#datascience #machinelearning #math Timing Breakdown 0:00 - Intro & Overview 1:53 - Statistics & Probability 4:14 - Linear Algebra 6:10 - Mathematical Optimization 8:28 - Calculus 11:05 - Specific data Science tasks & math you need to know for them 13:33 - Final Thoughts ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld 🍓🍍JUICY LINKS FROM VIDEO🍍🍓 Definition of statistics: https://www.merriam-webster.com/dictionary/statistics Definition of probability: https://en.wikipedia.org/wiki/Probability Statistics terms for data science summary: https://towardsdatascience.com/probability-and-statistics-for-data-science-part-1-3eed6051c40d Probability terms for data science summary: https://www.analyticsvidhya.com/blog/2017/02/basic-probability-data-science-with-examples/ Definition of Linear Algebra: https://www.merriam-webster.com/dictionary/linear%20algebra Basic Linear algebra term definitions: https://towardsdatascience.com/basics-of-linear-algebra-for-data-science-9e93ada24e5c# Mathematical Optimization Definition: https://en.wikipedia.org/wiki/Mathematical_optimization Optimizations in machine learning: https://towardsdatascience.com/demystifying-optimizations-for-machine-learning-c6c6405d3eea https://serokell.io/blog/ml-optimization Calculus for Data Science: https://towardsdatascience.com/calculus-in-data-science-and-its-uses-3f3e1b5e5b35 Math in deep learning: https://towardsdatascience.com/introduction-to-math-behind-neural-networks-e8b60dbbdeba Experimental Design: https://www.scribbr.com/methodology/experimental-design/ Another take on the math you need for data science: https://medium.com/s/story/essential-math-for-data-science-why-and-how-e88271367fbd Anotha one: https://www.kdnuggets.com/2018/09/essential-math-data-science.html

TIMING BREAKDOWN: Lesson 1 - 1:37 Lesson 2 - 5:24 Lesson 3 - 7:49 Lesson 4 - 10:28 Lesson 5 - 12:51 (Bonus Lesson) Final Thought - 15:10 If you've ever felt unworthy of your accomplishments, join me as I share 5 lessons that helped me overcome a decade of imposter syndrome: as a STEM student in university, as a data scientist in the tech industry and as human being on planet earth. ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld 🍓🍍JUICY LINKS FROM VIDEO 🍓🍍 What is Imposter Syndrome: https://www.verywellmind.com/imposter-syndrome-and-social-anxiety-disorder-4156469 2020 Imposter Syndrome Study: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174434/ Dunning-Kruger Effect and Imposter Syndrome: https://neurofied.com/the-dunning-kruger-effect/ #impostersyndrome #personaldevelopment #selfconfidence

#datascience #softwareengineering #techcareers 🍍🍓JUICY LINKS🍓🍍 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld RELATED VIDEOS What is a Data Scientist Video? https://youtu.be/E1pNOqyq8s8 Additional Resources by people who aren’t me: https://data-flair.training/blogs/data-scientist-vs-data-engineer-vs-data-analyst/ https://www.kdnuggets.com/2015/11/different-data-science-roles-industry.html https://blog.udacity.com/2018/01/4-types-data-science-jobs.html https://towardsdatascience.com/what-kind-of-data-science-role-is-right-for-you-9d2f4b117e81 https://www.northeastern.edu/graduate/blog/data-analytics-vs-data-science/ https://www.edureka.co/blog/data-analyst-vs-data-engineer-vs-data-scientist/ https://www.simplilearn.com/data-analyst-vs-data-scientist-article

Are you tired of getting rejected for tech internships? Say no more, fam! Big sis is here to tell you about how you can do it, no matter how un-hirable you appear on paper at this moment. 😉 Video Timing Breakdown 1:24 - Mistake 1 5:40 - Mistake 2 9:06 - Mistake 3 (including networking tips) 15:01 - Pro Tips 🍍JUICY LINKS 🍍 ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld LINKS FOR SOURCES MENTIONED IN VIDEO Side project Ideas: https://www.codementor.io/@npostolovski/40-side-project-ideas-for-software-engineers-g8xckyxef Github Pages: free way to host simple websites - https://pages.github.com/ How to make a good technical resume: https://www.youtube.com/watch?v=NlDYJ_eSVx0&t=77s Reliable Tech Internship Listings: https://github.com/pittcsc/Summer2021-Internships https://github.com/ChrisDryden/Canadian-Tech-Internships-Summer-2021 https://nodesk.co/remote-jobs/internship/ Job Hunt Statistics: https://www.linkedin.com/pulse/new-survey-reveals-85-all-jobs-filled-via-networking-lou-adler/ https://money.usnews.com/money/blogs/outside-voices-careers/2014/09/17/dont-believe-these-8-job-search-myths https://www.themuse.com/advice/6-insider-job-search-facts-thatll-make-you-rethink-how-youre-applying My favourite job forums: Angel.co Linkedin.com Networking events: Meetup.com #tech #internships #jobhunt #networking #careeradvice

Watch this if you’re considering data science as a career - giving you the inside scoop on what it’s like to work as one so you know if it’s right for you! ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld Some articles pictured in the video: https://towardsdatascience.com/data-science-has-become-too-vague-538899bab57 https://towardsdatascience.com/dear-companies-your-data-science-job-descriptions-are-awful-57a951d8c56b SQL practice site: https://sqlzoo.net/ Learning Python for Data Science: https://www.kdnuggets.com/2019/06/python-data-science-right-way.html #datascience #dayinthelife #tech

SO many juicy links to help you on your journey (you can thank me by liking, subscribing and sharing ;) ) ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld OTHER LINKS - MENTIONED IN VIDEO Titanic Classifier Project on Kaggle: https://www.kaggle.com/c/titanic Data Science project ideas: https://dev.to/anujgupta/50-top-data-science-project-ideas-for-beginners-and-experts-a3d Public datasets: https://github.com/awesomedata/awesome-public-datasets Scraping data from the web: https://towardsdatascience.com/web-scraping-make-your-own-dataset-cc973a9f0ee5 Pandas profiling - an EDA Python Library: https://github.com/pandas-profiling/pandas-profiling Data prep for machine learning: https://towardsdatascience.com/data-preparation-for-machine-learning-cleansing-transformation-feature-engineering-d2334079b06d Feature Scaling / Standardization and Normalization: https://www.analyticsvidhya.com/blog/2020/04/feature-scaling-machine-learning-normalization-standardization/ Feature Engineering: https://machinelearningmastery.com/discover-feature-engineering-how-to-engineer-features-and-how-to-get-good-at-it/ Dimensionality Reduction: https://machinelearningmastery.com/dimensionality-reduction-for-machine-learning/ Choosing a machine learning algorithm: https://www.kdnuggets.com/2019/10/choosing-machine-learning-model.html K-Fold Cross Validation: https://machinelearningmastery.com/k-fold-cross-validation/ Hyperparameter Tuning: https://towardsdatascience.com/hyperparameter-tuning-c5619e7e6624 Grid Search: https://medium.com/fintechexplained/what-is-grid-search-c01fe886ef0a https://scikit-learn.org/stable/modules/grid_search.html Feature Selection: https://machinelearningmastery.com/feature-selection-with-real-and-categorical-data/ Feature Importances: https://scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html https://towardsdatascience.com/explaining-feature-importance-by-example-of-a-random-forest-d9166011959e Choosing a performance metric: https://www.kdnuggets.com/2018/06/right-metric-evaluating-machine-learning-models-2.html Model Deployment Flask - a microweb framework for Python, great for wrapping your model into a web app: https://opensource.com/article/18/4/flask Deploying ML models with Flask and Heroku: https://medium.com/analytics-vidhya/deploy-machinelearning-model-with-flask-and-heroku-2721823bb653 Deploying Machine Learning Models on GCP: https://heartbeat.fritz.ai/deploying-machine-learning-models-on-google-cloud-platform-gcp-7b1ff8140144 #datascience #machinelearning #codingproject #pythonproject

The ultimate guide to cracking the data science interview! Breaking down the process, the questions you’ll be asked and how to prepare so that you kill it every. single. time. ** note: the links below are affiliate links, meaning I receive a small referral commission FIND A SUPER COOL DATA SCIENCE MENTOR https://www.sharpestminds.com/?r=damsel MY RECOMMENDED DATA SCIENCE COURSERA COURSES Professional Data Science Certificate (IBM): https://coursera.pxf.io/QOvm49 Python for Everybody (University of Michigan): https://coursera.pxf.io/kj1BZv Machine Learning (Stanford): https://coursera.pxf.io/e45Vg6 Statistics with Python (University of Michigan): https://coursera.pxf.io/Gj4zG6 And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers: Data Structures and Algorithms (UC San Diego) - https://coursera.pxf.io/rnq6Ld OTHER LINKS - RESOURCES MENTIONED IN VIDEO: Technical Interview Tips https://www.womenwhocode.com/blog/cracking-the-coding-interview-10-questions-and-answers?mc_cid=fe4e44a4d3&mc_eid=fb8fa6a9a4 https://www.womenwhocode.com/blog/do-s-and-don-ts-of-technical-interviews?mc_cid=fe4e44a4d3&mc_eid=fb8fa6a9a4 Coding practice (python / algorithms) - https://leetcode.com/ SQL practice / review -https://sqlzoo.net/wiki/SQL_Tutorial Data science business problems and practice - https://www.kaggle.com/ #datascience #technicalinterview #interviewprep