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N150,000 Job Or Fully Funded Scholarship For Masters In Malaysia / Two Men Electrocuted In Kaduna While Working On A Streetlight / looking for the best ICT Center To Acquire pratical Skills In Kaduna (2) (3) (4)
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Scholarship For Software Coding & Web Development In Kaduna State by DomineIctHubs: 3:13pm On Aug 16, 2021 |
DOMINE ICT ACADEMY Yy5 Abuja Road By Lagos Street R/About, Kaduna. Email: domineicthubs@gmail.com Tel: 08036949015, 07045598289; 08068765146 To help you remain a competitive job candidate, here are some of the top skills you should prepare for to land you that dream job: 1. Full Stack Java developer Core Java + JSP Servlets + Hibernate +Spring + Java Web-service/RestFul API + Spring boot 2. Python and Django Full Stack Web Developer Learn to build websites with HTML, CSS, Bootstrap, JavaScript, jQuery, Python 3, and Django! 3. Full Stack Web Developer Learn HTML 5, CSS 3, JavaScript, Bootstrap 4, Media Queries, PHP, OOP, MYSQL, Database 4. Net Core Full Stack Developer C#, Asp.Net Core,Typescript.js, Angular Js, Database Development 5. Data Sciences & Data Analytics What You Will Learn Find out how to grab and load data into an analysis environment. Perform descriptive analysis to extract meaningful summaries from data. Discover probability, parameter estimation, hypothesis tests, and experiment design best practices. Get to grips with resampling and bootstrapping in Python Delve into statistical tests with variance analysis, time series analysis, and A/B test examples. Understand the statistics behind popular machine learning algorithms. Modules Module 1: Getting Started with Statistics for Data Science Module 2: Fundamentals of Data Collection, Cleaning, and Preprocessing Module 3: Essential Statistics for Data Assessment Module 4: Visualization with Statistical Graphs Module 5: Essentials of Statistical Analysis Module 6: Sampling and Inferential Statistics Module 7: Common Probability Distributions Module 8: Parametric Estimation Module 9: Statistical Hypothesis Testing Module 10: Statistics for Machine Learning Module 11: Statistics for Regression Module 12: Statistics for Classification Module 13: Statistics for Tree-Based Methods Module 14: Statistics for Ensemble Methods
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