C# Coding Interview Problems Masterclass
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C# Coding Interview Problems Masterclass
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 61 lectures (15h 53m) | Size: 5.92 GB
Master solving coding challenge questions from HackerRank, LeetCode, and CoderPad from beginner through advanced in C#!
What you'll learn:
Features my former professor and good friend, Eric Nersesian, who brings 12 years of industry and 6 years of teaching experience and expertise in software engineering
Be able to answer coding interview questions with confidence and take the guesswork out of programming
Understand how to approach a problem, plan the solution, implement it, refactor it, and test it and how to discuss Big-O notation with the interviewer
Obtain mastery over data structures and algorithms and understand the ideal time to use each different one in a coding interview
Learn techniques to optimize your code, write clean code, and make the code you write more readable
Build a debugging skillset you can use when you stumble in an interview, and understand how to recover with confidence to impress the interviewer
Get comfortable programming with HackerRank, LeetCode, and CoderPad the three main platforms used by companies for coding interviews
Understand the "never give up" mentality and how to tackle coding interview questions that are complex, and how to maximize your chances at landing a job
Understand how to work with Linked Lists, Trees, and Graphs, the three most common advanced data structures asked about on coding interviews and understand how they work and when to use each
Learn how to solve problems with recursion, and understand when to use recursion and when to use iterative coding in an interview
Learn the process for breaking hard questions down into easier sub problems
Be able to implement Depth First Search and Breadth First Search algorithms
Master solving tree questions with generic trees, binary trees, and binary search trees
Learn to think like a computer programmer
Understand how to do pre-order, in-order, and post-order traversal on trees
Get experience solving coding questions with matrices and multi-dimensional arrays
Requirements
Working knowledge of C#
Desire to learn how to approach coding interview problems and competitive programming challenge questions
Description
This course has one goal: teach you how to ace coding interviews and challenging coding questions confidently and effectively to maximize your chances at landing your dream job. All of the solutions are programmed using C#, one of the most popular languages in the world.
What types of questions do you find challenging on interviews? Maybe you dread the infamous binary search tree questions. Or perhaps linked lists are the bane of your existence. Balanced braces, anyone?
You'll hear two voices in this course, one is mine and the other is that of a good friend, Eric Nersesian. Eric has a PhD in Informatics and specializes in software engineering and 3D graphics. With 12 years industry experience and 6 years as a professor at NJIT, he brings a myriad of knowledge and experience to this course.
On Udemy, you will find plenty of courses that teach you how to code. However, finding a course that teaches you how to ace interview problems for programming and teaches you how to approach each question is rare, and that is what this course is. There is no one, two, or three step approach to acing a coding interview. Don't believe the books and videos that tell you they will land you a dream job in a specific number of steps. Coding is hard, and it takes a lot of practice to get good at it. Moreover, interviews usually put a time limit on a question, so you might have 30 minutes to solve a question that would take most people a few hours at best.
In this course, Eric and I don't jump right to the keyboard after reading a question. We break down the problem and plan an approach - usually more than one approach - and then talk out our logic step-by-step. Some of these questions we've never seen before this, we actually solve them for the first time right before your eyes. This means that we don't always get the solution on the first try of running our code. This is good, because you see how to push forward and debug, refactor, and keep a level head under pressure by watching how we do it. At the end of the day, we are two industry professionals that love to code.
Have you ever had a coding interview that didn't go so well? Are you nervous for your next coding test? If you want to approach your next programming interview with confidence, then enroll now!
Who this course is for
Anyone that wants to improve their knowledge of data structures and algorithms
Anyone that wants to learn how to ace coding tests and interviews
Professional programmers that want to improve their coding interview skills
Students interested in competitive programming or preparing for a coding test
Developers that will be interviewing candidates for their company and want to learn how to ask good coding challenge questions
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/c-coding-interview-problems-masterclass/
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Code:
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Traffic Think Tank Academy
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Traffic Think Tank Academy
MP4 | Video: 1152 x720 | Audio: AAC 48 Khz , 2ch | Duration: 90 hours | Language: English | 30.3 GB
You never have to feel stuck, alone, or stagnant in SEO again. You're serious about growing in SEO. But like everyone, you're sick of wasting hours on half-baked blogs, noisy Facebook groups full of self-promoters, and mediocre courses that don't deliver. Almost none of it is helpful or specific enough to YOU. So, you tread water. Nothing changes.
But algo updates,
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So you can finally feel like you're ahead of the game (instead of barely keeping up.)
How much further
would you be.
.if you could get help with any challenge on-demand from smart people who've been there? Like being handed the blueprint a top expert is using right now to get results?
Imagine having the "Who's Who" of SEO chime in to help-or becoming one of the "Who's Who" yourself!
That's Traffic Think Tank.
It's not another static course or flaky group. It's the all-in-one Accelerator you need to keep growing, no matter how advanced or new you are now.
The Academy is your go-to resource for solutions to every common challenge. The Mastermind is like having a lifeline on "Who Wants to Be a Millionaire?" for the questions no course can cover.
It's like having a boardroom
full of smart mentors
available 24/7
"TTT-ers" share what they know. They send each other work. They team up on projects, clink glasses, and hang out in real life.
You can literally buy yourself a ticket to the "Inner Circle" of SEO and put networking on 'easy mode.'
If you've ever said,
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Join Traffic Think Tank. By this time next week, you'll have answers to the toughest challenges you're facing, an Academy full of exclusive resources published by top experts, and a community of friends and mentors to help you as you grow.
Get the "golden nuggets" on topics like:
Link building at scale or on a budget Conducting keyword research in 2021 How to track and report KPIs Content creation that drives qualified leads Strategies for local SEO in a changing SERP Scaling up your team without losing your mind Solving complex technical SEO issues Building processes that work at any level How to prove and sell your value to a client or boss
Where do you want to grow next?
Link Building
Learn how to build links at scale and on a budget, from prospecting to outreach.
Content Marketing
Get step-by-step processes for planning, creating, and promoting content that wins.
Keyword Research
See how the experts are finding their best targets in 2020 and beyond.
Technical SEO
Get in the weeds and learn how to tackle technical issues with total confidence.
Analytics & Reporting
Sharpen you analytics skills and know what to look for with clear, practical guidance.
Agency Ops
Learn how respected experts scale their agency processes, teams, and revenue.
Local SEO
Snap up attention, rankings, and traffic in your local market with proven how-tos
Affiliate
Step behind the scenes to see how successful affiliates build and profit from their money sites.
Conversion Optimization
Make the most of the traffic you earn with actionable insights anyone can use.
Course Content:
2020 Summary
7 Figure Agency
Agency Growth
An Introduction to Paid Acquisition
An Introduction to Technical SEO
Analytics & Reporting
App Store Optimization (ASO) & Mobile
Automation for SEO
Building & Earning Backlinks
Building Local Directory Sites
Buying Growth How to Successfully Acquire a Website
Canary Sites
Cohort Keyword Research
Content Promotion
Content Strategy
Conversion Rate Optimization
Creating a Money Site from Scratch
Google Updates & Penalties
International SEO
Introduction to Google Data Studio
Keyword Research
Live Q&As
Local SEO
On-Page Optimization
Traffic Think Tank Live 2020
Website & Domain Acquisitions
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Code:
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Learn Java Collection Framework and Generics in Simple Way
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Learn Java Collection Framework and Generics in Simple Way
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 89 lectures (17h 18m) | Size: 20.2 GB
Direct Class Room Videos to get complete knowledge on Java Collection Framework and Generics
What you'll learn:
Students can get complete in-depth knowledge on java concepts like Java Collection Framework and Generics concepts
Requirements
Basic Idea on Computer
Description
Payed Courses:
1. Complete Core Java in Simple Way
2. Complete Core Java In Simple Way Part-2
3. Learn Object Oriented Programming (OOPs) Concepts in Java
4. Learn Java Multithreading In Simple Way
5. Advanced Java (JDBC,Servlets,JSP,JSTL) For Web Development
6. Learn Java Collection Framework and Generics in Simple Way [New]
Free Courses:
1. Learn Java Wrapper Classes in Simple Way - Free Course
2. Learn 'this' Keyword in Java - Free Course
I will focus mainly on
1. Arrays
2. List and its implementations
3. Iterators/Cursors in Collections
4. Set and its Implementations
5. Comparable and Comparator
6. Queue and its Implementations
7. Map and its Implementations
8. Generics
Benefits of this course:
1. This Course will provide completeness on every topic.
2. This Course will make you to Strong on Theoritically and
Programmatically.
3. This Course will provide Good Platform for the AdvancedTechnologies
and Frameworks like Jdbc, Servlets, Jsps, Hibernate,
JPA, Spring,......
4. This Course includes almost all the interview Questions
and Answers as part of the Course internally.
5. This Course will provide Downloadable Material for all the
topics which are provided in Course Content.
Q) What are the differences between List and Set?
• List is index based, it able to allow all the elements as per indexing.
Set is not index based, it able to allow all the elements on the basis of elements hash code values.
• List is able to allow duplicate elements.
Set is not allowing duplicate elements.
• List is able to allow any number of null values.
Set is able to allow only one null value.
• List is following insertion order.
Set is not following insertion order by default.
Note: LinkedHashSet is following insertion order.
• List is not following sorting order.
Sets are not following sorting order by default.
Note: SortedSet, NavigableSet and TreeSet are following Sorting order.
• List is able to allow heterogeneous elements.
Sets are able to allow heterogeneous elements by default.
Note: SortedSett, NavigableSet and TreeSet are allowing only Homogeneous elements.
Collection:
• It is an interface provided by JAVA along with JDK 1.2 version.
• It able to represent a group of individual elements as single unit.
• It has provided the following methods common to every implementation class.
Who this course is for
Academic Students who are having Java Course in their Curriculum
Software Professionals who are very fancy about Java Programming
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/learn-java-collection-framework-and-generics-in-simple-way/
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Code:
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https://rapidgator.net/file/27911626688ee0f018ddfe54bc159305/Learn_Java_Collection_Framework_and_Generics_in_Simple_Way.part20.rar.html
Graph Theory Algorithms for Competitive Programming (2021)
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Graph Theory Algorithms for Competitive Programming (2021)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 96 lectures (20h 12m) | Size: 10.6 GB
Learn Graphs Algorithms in Computer Science & Mathematics, theory + hands-on coding and ace Competitive Coding problems!
What you'll learn:
Graph Basics, Applications
BFS, DFS, Connected Components
Shortest Paths - Dijkstra, Bellman, Floyd Warshall
Travelling Salesman Problem - DP with Bitmasks
Topological Ordering, Strongly Connected Components
Disjoint Set Union, Minimum Spanning Trees, Prim's & Kruskal
Advanced Graphs, Euler Tour, Trees
Network Flow, LCA, Articulation Points
Graphs for Competitive Programming
80 + Competitive Coding Questions
Requirements
Familiarity with basic data structures
Ability to write / understand code
Prior experience in problem solving
Description
Welcome to Graph Algorithms for Competitive Coding - the most detailed Specialisation in Graph Theory for Competitive Programmers, Software Engineers & Computer Science students!
Graphs is quite an important topic for software engineers, both for academics & online competitions and for solving real life challenges. Graph algorithms form the very fundamentals of many popular applications like - Google Maps, social media apps like Facebook, Instagram, Quora, LinkedIn, Computer Vision applications such as image segmentation, resolving dependencies while compile time, vehicle routing problems in supply chain and many more. This course provides a detailed overview of Graph Theory algorithms in computer science, along with hands on implementation of all the algorithms in C++. Not just that you will get 80+ competitive coding questions, to practice & test your skills!
This comprehensive course is taught by Prateek Narang & Apaar Kamal, who are Software Engineers at Google and have taught over thousands of students in competitive programming over last 5+ years. This course is worth thousands of dollars, but Coding Minutes is providing you this course to you at a fraction of its original cost! This is action oriented course, we not just delve into theory but focus on the practical aspects by building implementing algorithms & solving problems. With over 95+ high quality video lectures, easy to understand explanations this is one of the most detailed and robust course for Graph Algorithms ever created.
Course starts very basics with how to store and represent graphs on a computer, and then dives into popular algorithms & techniques for problem solving. The course is divided into two parts.
Part-I Graph Theory Essentials
Graph Representations
Popular Traversals - BFS & DFS
Cycle Detection - Weighted & Unweighted Graphs
Topological Ordering & Directed Acyclic Graphs
Disjoint Set Union, Path Compression & Union by Rank
Minimum Spanning Trees - Prim's & Kruskal's
Shortest Paths - BFS, Dijkstra's, Bellman Ford, Floyd Warshall
Travelling Salesman Problem, Min Cost Hamiltonian Cycle
Part-II Graph Theory Advanced
Flood Fill
Multisource BFS
DFS & Backedges
SCC's & Kosaraju's Algorithm
Euler Tour
LCA
Trees
Articulation Points & Bridges
Network Flow
The part-II is recommended for programmers who want to deep dive into Competitive Programming & take part in contests. For most students part-I is good enough to understand the most fundamental concepts and techniques in graphs!
Our special thanks to our problem setters, Siddharth Singhal & Rajdeep from Delhi Technological University, who helped us crafting the complete problem-set for this course.
So what you are waiting for ? Sign up today & start your deep-dive into graph theory!
Who this course is for
Intermediate-Advanced Programmers with basic coding experience
College/ University students pursuing Computer Science or related fields
Passionate programmers who want deep dive into Graph Theory
Competitive Programmers who want to excel in online coding competitions
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/graph-theory-algorithms-for-competitive-programming/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitro.download/view/0D3930920F6105B/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part01.rar
https://nitro.download/view/8009A1598D86F91/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part02.rar
https://nitro.download/view/19D118BC13109C5/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part03.rar
https://nitro.download/view/8F79F704096CFFD/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part04.rar
https://nitro.download/view/65F6985C552D9B1/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part05.rar
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https://nitro.download/view/3C2E8855D15043C/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part07.rar
https://nitro.download/view/CF53D34108903BA/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part08.rar
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https://nitro.download/view/9485A584F3229F9/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part11.rar
https://nitro.download/view/3AAF8E10DFE7033/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part12.rar
Code:
https://rapidgator.net/file/a425f0c13209c489d01a5bbdad18ea85/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part01.rar.html
https://rapidgator.net/file/b13ead5b8df51226f33fc1167545e034/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part02.rar.html
https://rapidgator.net/file/cb0d02936eccf9a748b2eed5ba5374e6/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part03.rar.html
https://rapidgator.net/file/e5a733bd2be6a79adfe36671fd396a14/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part04.rar.html
https://rapidgator.net/file/a70dcd2055f9e32ed706868d4b53642c/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part05.rar.html
https://rapidgator.net/file/ebc4c64059490d4bb09c91194c27a59b/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part06.rar.html
https://rapidgator.net/file/d74e6cf66ab0c160dd8838d0ffe12f54/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part07.rar.html
https://rapidgator.net/file/f177a2e7a25c7083556d9a9e07ac3695/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part08.rar.html
https://rapidgator.net/file/4bf788baff44e007b1a14669c51971ae/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part09.rar.html
https://rapidgator.net/file/03ee84f6869278a015a0642f99c5bb99/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part10.rar.html
https://rapidgator.net/file/d8e7dcd232544407a2c31a54347dd874/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part11.rar.html
https://rapidgator.net/file/7e33674c389869954892ab8478ff989f/Graph_Theory_Algorithms_for_Competitive_Programming_(2021).part12.rar.html
Udemy - Data Science with R
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Udemy - Data Science with R
Created by Uplatz Training | Published 7/2021
Duration: 23h 4m | 34 sections | 39 lectures | Video: 1280x720, 44 KHz | 11.5 GB
Genre: eLearning | Language: English + Sub
Learn Data Science using R from scratch. Build your career as a Data Scientist. Explore knitr, buzz dataset, adv methods
What you'll learn
Data Science using R programming
Become a Data Scientist
Data Science Learning Path
How to learn Data Science
Data Collection and Management
Model Deployment and Maintenance
Setting Expectations
Loading Data into R
Exploring Data in Data Science and Machine Learning
Exploring Data using R
Benefits of Data Cleaning
Cross Validation in R
Data Transformation
Modeling Methods
Solving Classification Problems
Working without Known Targets
Evaluating Models
Confusion Matrix
Introduction to Linear Regression
Linear Regression in R
Simple and Multiple Regression
Linear and Logistic Regression
Support Vector Machines (SVM) in R
Unsupervised Methods
Clustering in Data Science
K-means Algorithm in R
Hierarchical Clustering
Market Basket Analysis
MBA and Association Rule Mining
Implementing MBA
Association Rule Learning
Decision Tree Algorithm
Exploring Advanced Methods
Using Kernel Methods
Documentation and Deployment
Show more
Show less
Requirements
Enthusiasm and determination to make your mark on the world!
Description
Data Science includes various fields such as mathematics, business insight, tools, processes and machine learning techniques. A mix of all these fields help us in discovering the visions or designs from raw data which can be of major use in the formation of big business decisions. As a Data scientist it's your role to inspect which questions want answering and where to find the related data. A data scientist should have business insight and analytical services. One also needs to have the skill to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data.
R is a commanding language used extensively for data analysis and statistical calculating. It was developed in early 90s. R is an open-source software. R is unrestricted and flexible because it's an open-source software. R's open lines permit it to incorporate with other applications and systems. Open-source soft wares have a high standard of quality, since multiple people use and iterate on them. As a programming language, R delivers objects, operators and functions that allow employers to discover, model and envision data. Data science with R has got a lot of possibilities in the commercial world. Open R is the most widely used open-source language in analytics. From minor to big initiatives, every other company is preferring R over the other languages. There is a constant need for professionals with having knowledge in data science using R programming.
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Uplatz provides this comprehensive course on Data Science with R covering data science concepts implementation and application using R programming language.
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Data Science with R - Course Syllabus
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1. Introduction to Data Sciencee
1.1 The data science process
1.2 Stages of a data science project
1.3 Setting expectations
1.4 Summary
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[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitro.download/view/01AEBCBAD8579B7/DataSciencewithR.part01.rar
https://nitro.download/view/C67B4A2084B882A/DataSciencewithR.part02.rar
https://nitro.download/view/0CCCB7F537BFFD8/DataSciencewithR.part03.rar
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https://nitro.download/view/2633A00368C20F3/DataSciencewithR.part08.rar
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https://nitro.download/view/28B771BAE7B7AE0/DataSciencewithR.part10.rar
https://nitro.download/view/59D4D65CAB0DB9C/DataSciencewithR.part11.rar
https://nitro.download/view/FD25BD9F2274B79/DataSciencewithR.part12.rar
Code:
https://rapidgator.net/file/fe674e54ad5d3e22aa356d6a18c434c9/DataSciencewithR.part01.rar.html
https://rapidgator.net/file/9e10f002f1e2e64a3f9cd2366eccd018/DataSciencewithR.part02.rar.html
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https://rapidgator.net/file/5b470fad8747bd36c7459a1209587ce5/DataSciencewithR.part05.rar.html
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https://rapidgator.net/file/b251ac49558d1e551db25f87620d89f1/DataSciencewithR.part07.rar.html
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https://rapidgator.net/file/f51c105e4088f3ca6d9d15de76e89920/DataSciencewithR.part10.rar.html
https://rapidgator.net/file/73d9c5d9b4568d87d734f6c81e5c0791/DataSciencewithR.part11.rar.html
https://rapidgator.net/file/bacb4570bf8b7475a287c28fc7e6437e/DataSciencewithR.part12.rar.html
Uncle Rat's Bug Bounty Guide (Updated 06/2021)
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Uncle Rat's Bug Bounty Guide (Updated 06/2021)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 102 lectures (11h 24m) | Size: 7.74 GB
Take the leap from practice platform to bug bounty target
What you'll learn:
A Bug Hunters mindset, i won't hold your hand. This is bug bounties
A solid bug bounty methodology to help you get started
Several attack techniques and how to employ them
What parameters to test for what vulnerabilities
Requirements
Be farmiliar with the basics of web communication like GET,POST,PUT,DELETE... calls
A computer that can run burp suite, OS doesn't matter
Description
SUDO
I can not promise this course will find you bugs. I can promise i will leave you with a solid methodology that's netted me a few nice extra monthly salaries. This method is not guaranteed to work for you. You will need to adept. You will need to work.
If any course promises you that they WILL find you bugs, run as fast as you can.
WHOAMI
My name is uncle rat and i am here to help you take the next step. I am not here to hold your hand, i am here to push you over the edge. You've been practicing on pratice platforms for long enough now, don't you think? It's time.
I will provide you with a solid methodology to build upon. I don't want you to follow in my footsteps, i want you write your own legend. This is after all the place where legends are born.
Every chapter has at least a video file with slides to download and where applicable a full text PDF with extra information. All extra's like cheat sheets are seperatly downloadeable for your comfort.
- The XSS Rat
CAT 'goals.txt'
I can hack, but i can only hack one target at a time. My passion is teaching so why not hit two birds with one stone?
I created this course because i strongly believe that if i hack 1 target i am just me but if i train 1000 hackers, we are an army.
This is my goal, i want to make the internet a safer place but i can't do it alone.
Who this course is for
Beginner bug bounty hunters who are looking for a solid methodology and mindset
Experienced pentesters looking to get into bug bounties
Companies training their cybersecurity staff to withstand even the toughest of logic attacks
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/uncle-rats-bug-bounty-guide/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitro.download/view/0D12FDCB7949020/Uncle_Rat's_Bug_Bounty_Guide.part1.rar
https://nitro.download/view/47DC455511DA3D4/Uncle_Rat's_Bug_Bounty_Guide.part2.rar
https://nitro.download/view/EE39682B2C49C39/Uncle_Rat's_Bug_Bounty_Guide.part3.rar
https://nitro.download/view/56D23FA59D555F4/Uncle_Rat's_Bug_Bounty_Guide.part4.rar
https://nitro.download/view/9A1EB981F93990D/Uncle_Rat's_Bug_Bounty_Guide.part5.rar
https://nitro.download/view/2C77307092C976C/Uncle_Rat's_Bug_Bounty_Guide.part6.rar
https://nitro.download/view/854B01B491DB7B3/Uncle_Rat's_Bug_Bounty_Guide.part7.rar
https://nitro.download/view/E2EFCAE5DAB2838/Uncle_Rat's_Bug_Bounty_Guide.part8.rar
Code:
https://rapidgator.net/file/00c3610f227f118085695707b7399442/Uncle_Rat's_Bug_Bounty_Guide.part1.rar.html
https://rapidgator.net/file/4ab8ec7630b11c0584262a40670e4b72/Uncle_Rat's_Bug_Bounty_Guide.part2.rar.html
https://rapidgator.net/file/40525c9e58b1f6234fc6e0c28b47797b/Uncle_Rat's_Bug_Bounty_Guide.part3.rar.html
https://rapidgator.net/file/4988a958854756960c666fd19962787f/Uncle_Rat's_Bug_Bounty_Guide.part4.rar.html
https://rapidgator.net/file/75951e4c06bb0688a961963028e80234/Uncle_Rat's_Bug_Bounty_Guide.part5.rar.html
https://rapidgator.net/file/861d85d97f9db817e05f133f42587d5f/Uncle_Rat's_Bug_Bounty_Guide.part6.rar.html
https://rapidgator.net/file/3b655870b11ce550632002cfbade9d20/Uncle_Rat's_Bug_Bounty_Guide.part7.rar.html
https://rapidgator.net/file/4bce32e518f36c52cab1216e6c34b1fe/Uncle_Rat's_Bug_Bounty_Guide.part8.rar.html
Swift: Building Stocks App (2021 Swift)
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Swift: Building Stocks App (2021 Swift)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 6.08 GB | Duration: 7h 8m
Welcome to Building the Stocks App in Swift!
In this class you will learn to build a fully functional, high quality, and beautiful Stocks application for iOS with Swift 5, UIKit, and Xcode. You'll master several skills including the following:
Strong design skills for UI and architecture
Deep understanding of Swift and UIKit
Creating User Interfaces programmatically
Writing testable, clean, and documented code
Configuring and fetching data from remote API
Much More
Throughout our lessons, we will iterate on build the app together. You'll get a step by step walkthrough from Afraz, your Teacher, as to how to build each piece.
Alongside the video lessons, you can participate in the Class Project and build your own Stocks app. Share it here on Skillshare for everyone else to see! Don't forget to customize your project however you'd like to stand out and put those newly acquired skills to the test!
Let's get building.
Homepage
Code:
https://anonymz.com/?https://www.skillshare.com/classes/Swift-Building-Stocks-App-2021-Swift-%E2%9C%85/850494062
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitro.download/view/FE919D60F09D717/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part1.rar
https://nitro.download/view/D7984CA4B1774E4/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part2.rar
https://nitro.download/view/8B0AF1093B37E2B/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part3.rar
https://nitro.download/view/4B07D7DE65C7341/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part4.rar
https://nitro.download/view/53556420DC0BC1C/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part5.rar
https://nitro.download/view/30DDC3A88D221CD/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part6.rar
https://nitro.download/view/C34B1699DD4108D/Swift_Building_Stocks_App_(2021_Swift)_%E2%9C%85.part7.rar
Code:
https://rapidgator.net/file/e103a42b37af6396ac6bb1456424e14a/Swift_Building_Stocks_App_(2021_Swift)_✅.part1.rar.html
https://rapidgator.net/file/fad00e536cf66b6818d4539b308581cc/Swift_Building_Stocks_App_(2021_Swift)_✅.part2.rar.html
https://rapidgator.net/file/b192d887090212ea03b29230545808ec/Swift_Building_Stocks_App_(2021_Swift)_✅.part3.rar.html
https://rapidgator.net/file/4c8c2b5392301a1629161ddd96a95d65/Swift_Building_Stocks_App_(2021_Swift)_✅.part4.rar.html
https://rapidgator.net/file/254f4ceef7435bab3005b5f647903138/Swift_Building_Stocks_App_(2021_Swift)_✅.part5.rar.html
https://rapidgator.net/file/206390469c37b30b94edddb2cba9e595/Swift_Building_Stocks_App_(2021_Swift)_✅.part6.rar.html
https://rapidgator.net/file/c3d3ccbf8969154f63a145f22d6f844b/Swift_Building_Stocks_App_(2021_Swift)_✅.part7.rar.html
Making Handmade Glass Jewelry
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Making Handmade Glass Jewelry
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 5.24 GB | Duration: 4h 4m
What you'll learn
How to create glass jewelry
Requirements
no
Description
Glass jewelry can be colorful and bold, and it should be matched with the wardrobe. Although you may think otherwise, most glass jewelry isn't fragile. Most of it is created by applying heat to glass rods. This way, artists can make glass earrings, glass beads, pendants and glass rings. Alternatively, artisans can mold the glass into a pendant or a ring. Jewelry creators often choose glass for their creations. Glass for jewelry comes in many shapes and colors. As jewelry creator you can use simple glass beads or the beautiful Venetian Millefiori beads with embedded flowers. Each piece of glass jewelry is unique, therefore the jewelry you create is truly one of a kind. Jewelry making is a viable low investment business and jewelry making is one of the most popular items sold online. Try to research trends in order to choose what type of jewelry will sell. Read fashion and jewelry blogs and publications and follow influencers to get an idea of what to create. Think about packaging, logo, and website design for your jewelry brand. Product photography is also an important aspect you should think of for your online store. Good pictures of the items will bring more buyers and increase the sales.
Who this course is for:
People who like making beautiful handmade jewelry that they want to sell.
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/making-handmade-glass-jewelry/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitro.download/view/2A6397EC9503690/Making_Handmade_Glass_Jewelry.part1.rar
https://nitro.download/view/62FCFF3DA6C82A3/Making_Handmade_Glass_Jewelry.part2.rar
https://nitro.download/view/940E1E2C6089B56/Making_Handmade_Glass_Jewelry.part3.rar
https://nitro.download/view/9C024D1CAF5E8AF/Making_Handmade_Glass_Jewelry.part4.rar
https://nitro.download/view/2EC3217900F9A25/Making_Handmade_Glass_Jewelry.part5.rar
https://nitro.download/view/7188FF7B13E0597/Making_Handmade_Glass_Jewelry.part6.rar
Code:
https://rapidgator.net/file/cdf29f07dbc8571b99ce8c55469626e0/Making_Handmade_Glass_Jewelry.part1.rar.html
https://rapidgator.net/file/30db5e1a54d75ecbcc53aef0711b5884/Making_Handmade_Glass_Jewelry.part2.rar.html
https://rapidgator.net/file/a63b7c030027da438dedf47fb9560711/Making_Handmade_Glass_Jewelry.part3.rar.html
https://rapidgator.net/file/7fa667ca7b1fe382e173fc154314b278/Making_Handmade_Glass_Jewelry.part4.rar.html
https://rapidgator.net/file/53a52a52e24a9a526f343681a6303ee6/Making_Handmade_Glass_Jewelry.part5.rar.html
https://rapidgator.net/file/1999cb8222e2b25fdac74f4c64b1baf7/Making_Handmade_Glass_Jewelry.part6.rar.html
Complete Data Science, Deep Learning, R | Data Science 2021
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Complete Data Science, Deep Learning, R | Data Science 2021
Duration: 23h 12m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 6.9 GB
Genre: eLearning | Language: English
Data Science A-Z, Python for Data Science, R for Data Science, Statistics for Data Science, Math for Deep Learning
What you'll learn
Python
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Fundamental stuff of Python and its library Numpy
What is the AI, Machine Learning and Deep Learning
History of Machine Learning
Turing Machine and Turing Test
The Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etc.
What is Artificial Neural Network (ANN)
Anatomy of NN
Tensor Operations
Python instructors on Udemy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels.
Machine learning isn't just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you're a marketer, video game designer, or programmer, I am here to help you apply machine learning to your work.
The Engine of NN
Keras
Tensorflow
Convolutional Neural Network
Recurrent Neural Network and LTSM
Transfer Learning
Machine Learning
Deep Learning
Machine Learning with Python
Python Programming
Deep Learning with Python
If you have some programming experience, Python might be the language for you
Learn Fundamentals of Python for effectively using Data Science
Data Manipulation
Learn how to handle with big data
Learn how to manipulate the data
Learn how to produce meaningful outcomes
Learn Fundamentals of Python for effectively using Data Science
Numpy arrays
Series and Features
Combining Dataframes, Data Munging and how to deal with Missing Data
How to use Matplotlib library and start to journey in Data Visualization
Also, why you should learn Python and Pandas Library
Learn Data Science with Python
Examine and manage data structures
Handle wide variety of data science challenges
Select columns and filter rows
Arrange the order and create new variables
Create, subset, convert or change any element within a vector or data frame
Transform and manipulate an existing and real data
The Logic of Matplotlib
What is Matplotlib
Using Matplotlib
Pyplot - Pylab - Matplotlib
Figure, Subplot, Multiplot, Axes,
Figure Customization
Data Visualization
Plot Customization
Grid, Spines, Ticks
Basic Plots in Matplotlib
Seaborn library with these topics
What is Seaborn
Controlling Figure Aesthetics
Color Palettes
Basic Plots in Seaborn
Multi-Plots in Seaborn
Regression Plots and Squarify
Geoplotlib with these topics
What is Geoplotlib
Tile Providers and Custom Layers
R and Python in the same course. You decide which one you would go for!
R was built as a statistical language, it suits much better to do statistical learning and R is a statistical programming software favoured by many academia
Since R was built as a statistical language, it suits much better to do statistical learning. It represents the way statisticians think pretty well, so anyone with a formal statistics background can use R easily. Python, on the other hand, is a better choice for machine learning with its flexibility for production use, especially when the data analysis tasks need to be integrated with web applications. If you enroll this course you will have a chance to learn both
You will learn R and Python from scratch
Because data can mean an endless number of things, it's important to choose the right visualization tools for the job.
you're interested in learning Tableau, D3 js, After Effects, or Python, has a course for you.
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Machine Learning, and more!
Requirements
No prior knowledge is required
Free software and tools used during the course
Basic computer knowledge
Desire to learn data science
Nothing else! It's just you, your computer and your ambition to get started today
Description
Welcome to Complete Data Science, Deep Learning, R | Data Science 2021 course.
Ready for the Data Science career?
Are you curious about Data Science and looking to start your self-learning journey into the world of data ?
Are you an experienced developer looking for a landing in Data Science!
In both cases, you are at the right place!
The two most popular programming tools for data science work are Python and R at the moment. It is hard to pick one out of those two amazingly flexible data analytics languages. Both are free and open-source.
R for statistical analysis and Python as a general-purpose programming language. For anyone interested in machine learning, working with large datasets, or creating complex data visualizations, they are absolutely essential.
With my full-stack Data Science course, you will be able to learn R and Python together.
If you have some programming experience, Python might be the language for you. R was built as a statistical language, it suits much better to do statistical learning with R programming.
But do not worry! In this course, you will have a chance to learn both and will decide to which one fits your niche!
Throughout the course's first part, you will learn the most important tools in R that will allow you to do data science. By using the tools, you will be easily handling big data, manipulate it, and produce meaningful outcomes.
Throughout the course's second part, we will teach you how to use the Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Python for Data Science course.
We will open the door of the Data Science world and will move deeper. You will learn the fundamentals of Python and its beautiful libraries such as Numpy, Pandas, and Matplotlib step by step. Then, we will transform and manipulate real data. For the manipulation, we will use the tidyverse package, which involves dplyr and other necessary packages.
At the end of the course, you will be able to select columns, filter rows, arrange the order, create new variables, group by and summarize your data simultaneously.
Because data can mean an endless number of things, it's important to choose the right visualization tools for the job. Whether you're interested in learning Tableau, D3.js, After Effects, or Python, Udemy has a course for you.
In this course we will learn what is the data visualization and how does it work with python.
This course has suitable for everybody who interested data vizualisation concept.
First of all, in this course we will learn some fundamentals of pyhton, and object oriented programming ( OOP ). These are our first steps in our Data Visualisation journey. After then we take a our journey to Data Science world. Here we will take a look data literacy and data science concept. Then we will arrive at our next stop. Numpy library. Here we learn the what is numpy and how we can use it. After then we arrive at our next stop. Pandas library. And now our journey becomes an adventure. In this adventure we'll enter the Matplotlib world then we exit the Seaborn world. Then we'll try to understand how we can visualize our data, data viz. But our journey won't be over. Then we will arrive our final destination. Geographical drawing or best known as Geoplotlib in tableau data visualization.
Learn python and how to use it to python data analysis and visualization, present data. Includes tons of code data vizualisation.
In this course, you will learn data analysis and visualization in detail.
Also during the course you will learn:
The Logic of Matplotlib
What is Matplotlib
Using Matplotlib
Pyplot - Pylab - Matplotlib - Excel
Figure, Subplot, Multiplot, Axes,
Figure Customization
Plot Customization
Grid, Spines, Ticks
Basic Plots in Matplotlib
Overview of Jupyter Notebook and Google Colab
Seaborn library with these topics
What is Seaborn
Controlling Figure Aesthetics
Color Palettes
Basic Plots in Seaborn
Multi-Plots in Seaborn
Regression Plots and Squarify
Geoplotlib with these topics
What is Geoplotlib
Tile Providers and Custom Layers
In this course you will learn;
How to use Anaconda and Jupyter notebook,
Fundamentals of Python such as
Datatypes in Python,
Lots of datatype operators, methods and how to use them,
Conditional concept, if statements
The logic of Loops and control statements
Functions and how to use them
How to use modules and create your own modules
Data science and Data literacy concepts
Fundamentals of Numpy for Data manipulation such as
Numpy arrays and their features
How to do indexing and slicing on Arrays
Lots of stuff about Pandas for data manipulation such as
Pandas series and their features
Dataframes and their features
Hierarchical indexing concept and theory
Groupby operations
The logic of Data Munging
How to deal effectively with missing data effectively
Combining the Data Frames
How to work with Dataset files
And also you will learn fundamentals thing about Matplotlib library such as
Pyplot, Pylab and Matplotlb concepts
What Figure, Subplot and Axes are
How to do figure and plot customization
Examining and Managing Data Structures in R
Atomic vectors
Lists
Arrays
Matrices
Data frames
Tibbles
Factors
Data Transformation in R
Transform and manipulate a deal data
Tidyverse and more
This course has suitable for everybody who interested in Machine Learning and Deep Learning concepts in Data Science.
First of all, in this course, we will learn some fundamental stuff of Python and the Numpy library. These are our first steps in our Deep Learning journey. After then we take a little trip to Machine Learning Python history. Then we will arrive at our next stop. Machine Learning in Python Programming. Here we learn the machine learning concepts, machine learning a-z workflow, models and algorithms, and what is neural network concept. After then we arrive at our next stop. Artificial Neural network. And now our journey becomes an adventure. In this adventure we'll enter the Keras world then we exit the Tensorflow world. Then we'll try to understand the Convolutional Neural Network concept. But our journey won't be over. Then we will arrive at Recurrent Neural Network and LTSM. We'll take a look at them. After a while, we'll trip to the Transfer Learning concept. And then we arrive at our final destination. Projects in Python Bootcamp. Our play garden. Here we'll make some interesting machine learning models with the information we've learned along our journey.
In this course, we will start from the very beginning and go all the way to the end of "Deep Learning" with examples.
The Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etc.
Before we start this course, we will learn which environments we can be used for developing deep learning projects.
Artificial Neural Network with these topics
What is ANN
Anatomy of NN
Tensor Operations
The Engine of NN
Keras
Tensorflow
Convolutional Neural Network
Recurrent Neural Network and LTSM
Transfer Learning
Reinforcement Learning
And we will do many exercises. Finally, we will also have 4 different final projects covering all of Python subjects.
Why would you want to take this course?
Our answer is simple: The quality of teaching.
When you enroll, you will feel the OAK Academy's seasoned instructors' expertise.
Fresh Content
It's no secret how technology is advancing at a rapid rate and it's crucial to stay on top of the latest knowledge. With this course, you will always have a chance to follow the latest data science trends.
Video and Audio Production Quality
All our content is created/produced as high-quality video/audio to provide you the best learning experience.
You will be,
Seeing clearly
Hearing clearly
Moving through the course without distractions
You'll also get:
Lifetime Access to The Course
Fast & Friendly Support in the Q&A section
Udemy Certificate of Completion Ready for Download
Dive in now!
We offer full support, answering any questions.
See you in the course!
Who this course is for:
Anyone interested in data sciences
Anyone who plans a career in data scientist,
Software developer whom want to learn data science,
Anyone eager to learn Data Science with no coding background
Statisticians, academic researchers, economists, analysts and business people
Professionals working in analytics or related fields
Anyone who is particularly interested in big data, machine learning and data intelligence
Homepage
Code:
https://www.udemy.com/course/complete-data-science-deep-learning-r-data-science-2021
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