Impossible is nothing!
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
100Days
September 18, 2022 – September 29, 2022
This repo track my progress for the 100 day challenge Till 27 Dec'22 starting from 19 Sept'22 for upcoming Exams
View ProjectSampleJSONPlaceholder
July 6, 2022 – July 7, 2022
SampleJSONPlaceholder — GitHub repository
View ProjectDataLit-SchoolofAI-
January 28, 2019 – January 28, 2019
Data Lit is is a 3 month course designed to help absolute beginners become proficient in Data Science. Each week offers lessons on Data Science fundamentals applied to real-world problems that Data Scientists help solve. After completing this course, start applying for jobs, doing contract work, start your own data science consulting group, or just keep on learning. Remember to believe in your ability to learn. You can learn data science, you will learn data science, and if you stick to it, eventually you will master it. This course starts on January 28,2019. We’re building many, many lectures for each week, expect this curriculum to get much more detailed before the course starts. Sign up now! Components 2 Projects (1 Midterm + 1 Final) 1 Weekly assignment Course Length 12 Weeks 10-15 hours per week Certification Students who successfully complete the course will receive their own certificate signed by Siraj Raval. Tools Used Python, SQL, Tensorflow, Hadoop, MapReduce, Spark, GitHub
View ProjectCultural Fit Analysis
The candidate's projects show an interest in learning and exploring various technical areas, including data science, digital systems, and web development. The 'DataLit-SchoolofAI-' project indicates a proactive approach to self-learning in a structured course format. However, the projects are primarily personal and lack details on team collaboration or real-world impact, making a comprehensive cultural fit assessment difficult. The breadth of technologies mentioned across projects (Python, SQL, Tensorflow, VHDL, HTML, JavaScript, C++, TypeScript) suggests adaptability and a willingness to learn diverse tools.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, and there are no psychometric test results or interview notes.