Clarusway

Course Description:

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering lots of services from data centers globally. Millions of customers are using AWS to save costs, become more agile, and innovate faster. For that reason, AWS is preferred as a cloud service provider.

There are no prerequisites for this program. This program helps students to gain knowledge about various types of cloud technology roles with a method to validate their AWS Cloud knowledge to enhance their credibility as an IT professional, and also helps them to validate their ability to effectively demonstrate knowledge of how to build and deploy a secure and robust application using AWS technologies.

A three-week AWS Certified Cloud Practitioner and AWS Certified Solutions Architect certification exam preparation course will be given following the completion of the course.

Program Flow:
● AWS (16 Weeks)

Program Coverage:
● 140+ Hours In-class Training
● 18+ Hours Mentoring Service
● 57 Hours Lab/Project Sessions
● 33 Hours AWS Certification Exam Preparation
● 40+ Hands-on
● 6 Projects
● 1 Capstone Project
● CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
● Cloud Engineer
● AWS Solutions Architect
● Cloud Practitioner
● Site Reliability Engineer
● Cloud Architect
● Cloud Solutions Consultant

Eligibility:
● No 4-year degree required
● No previous coding experience required.

Subjects:
AWS, Systems Architecture, Cloud Computing

Course Description:

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering many services from data centers globally. Millions of customers are using AWS to save costs, become more agile, and innovate faster. For that reason, AWS is preferred as a cloud service provider.

After the AWS module, a 14-week DevOps training will be conducted. The skills you learn in our DevOps for Professionals Learning Path will enhance your qualifications and open more significant opportunities to significantly leverage your income as a much sought-after professional in the high-demand IT job market.

A three-week AWS Certified Cloud Practitioner and AWS Certified Solutions Architect certification exam preparation course will be given following the completion of the course.

Program Flow:
● AWS (16 Weeks)
● DevOps (14 Weeks)

Program Coverage:
● 270+ Hours In-class Training
● 36+ Hours Mentoring Service
● 80+ Hours Lab/Project Sessions
● 24 Hours AWS Certification Exam Preparation
● 80+ Hands-on
● 12 Projects
● 2 Capstone Projects
● CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
● DevOps Engineer
● Cloud Engineer with DevOps
● AWS Solutions Architect
● Cloud Solutions Consultant
● Cloud Architect
● SysOps Administrator
● Cloud Developer
● Cloud DevOps Engineer
● Platform Engineer
● Build Engineer
● Site Reliability Engineer
● Release Manager

Subjects:
AWS, DevOps, Systems Architecture, Cloud Computing

Course Description:

In this course, we aim to give accurate skills and talents to our students to have them deliver the products of the backend. After this course, our students will be able to:
• Develop applications with Python by using Django Framework running at the backend
• Design and use a database and integrate this database with APIs and Applications
• Develop APIs with Django Rest Framework including database support and deploy these APIs to popular servers
• Handle and ensure accessibility and security compliance such as user authentication and access control for an application working at the backend
• Make version control, such as Git

Program Flow:
● Backend (12 Week)

Program Coverage:
● 110 Hours in-class training
● 15 Hours Mentoring
● 50 Hours Lab/Project Sessions
● 6 Projects
● 1 Capstone Project
● CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
● Backend Developer
● Django Developer
● Python Developer

Eligibility: Basic level on GIT (if not participants may watch recorded videos on Git lessons before the course start date)

Subjects:
API, Python, Django, Back-End Web Development

Course Description:

This course consists of two modules: Blockchain Technology and Web3 Development. The program aims to meet the market demand for startups that focus on blockchain technology. Students will also learn how to build real-life applications towards the end of the program.

Blockchain Technology and Ecosystem Module: This module covers six topics, comprising Blockchain and Bitcoin, Smart Contracts and Ethereum, Oracle Problem, Decentralized Applications, and NFTs, and scalability problems and examples.

Web3 Development Module: Students who get the Web 3.0 Development module will learn how to build applications (dApps) on the blockchain with Javascript, HTML, CSS, and Solidity to become a Blockchain Engineer. Web 3.0 developer course module includes the following topics: Terminal, Git, HTML, CSS, Introduction to Web 3.0 Development, Javascript, Solidity, Web 3.0 Libraries, Chainlink, The Graph, and GraphQL.

Program Coverage:
● Technology Module:
○ Consensus Mechanisms and Key Concepts
○ Technology Behind Bitcoin: Blockchain
○ Smart Contracts and Ethereum
○ dApps, DAOs, and NFTs
○ Oracle Problem and Decentralized Oracle
○ Blockchain Scalability
○ Whitepaper Reading
○ User Interaction with Bitcoin
○ Bridges
○ Storages

● Development Module
○ IT Fundamentals for Blockchain
○ Introduction to Web 3.0 Development
○ Javascript
○ Solidity
○ Web 3.0 Development
○ The Graph
○ GraphQL
○ Chainlink

Eligibility:
● No 4-year degree required
● No IT Background Required

Targeted Job Title:
● Product Manager
● Marketing Specialist
● Consultant
● Content Lead
● Researcher
● Blockchain Engineer
● Blockchain Developer
● Solidity Engineer
● Smart Contract Developer
● Full-stack DeFi Developer

Subjects:
CSS, HTML, Blockchain, Web Development

Course Description:

This course was designed to provide a new career opportunity for beginners, while intermediate and advanced professionals can enhance their careers in Cyber Security roles.

The learning path starts with Cyber Security Fundamentals for beginners and continues with advanced topics including the CompTIA Security Plus exam.

Program Coverage:

MODULE-01 (8 weeks)
CompTIA Security Plus Certificate Training
● Introduction to IT & Cybersecurity
○ Computer Fundamentals
○ Network Fundamentals
● CompTIA Security Plus
○ Attacks, threats, and vulnerabilities
○ Architecture and design
○ Implementation
○ Operations and incident response
○ Governance, risk, and compliance
● CompTIA Security Plus Exam Preparation
○ Q&A Sessions

Eligibility:
● No 4-year degree required
● No previous coding experience required

Subjects:
CompTIA Security+

Course Description:

This course was designed to provide a new career opportunity for beginners, while intermediate and advanced professionals can enhance their careers in Cyber Security roles.

Cyber security attacks are becoming more prevalent worldwide, resulting in a scarcity of cyber security analysts. Cyber security experts help organizations prevent, detect and manage cyber threats by employing various tools, technologies, and processes.

It’s possible to enter the cyber security profession without a degree by starting in an entry-level IT position. You could then work your way up to a cyber security role by gaining experience and industry certifications.

This course will teach you which tools a cybersecurity analyst will most frequently use today and how they use them, and there will be many hands-on sessions on these tools. Then, shifts will be created on the tools used in the SOC, so that the trainees will have experience in the current SOC working environment.

Finally, the skills required for job applications will be gained in the Job Hunting section where job search processes, Resume/CV perfection, LinkedIn perfection, and mock interviews will be studied.

Program Coverage:
MODULE-01 (8 weeks)
CompTIA Security Plus Certification + Exam Prep.
● Introduction to IT & Cybersecurity
○ Computer Fundamentals
○ Network Fundamentals
● CompTIA Security Plus
○ Attacks, threats, and vulnerabilities
○ Architecture and design
○ Implementation
○ Operations and incident response
○ Governance, risk, and compliance
● CompTIA Security Plus Exam Preparation
○ Q&A Sessions

MODULE-02 (10 weeks)
Security Operation Center (SOC) Experience
● Real-time SOC Experience
● Security Operations Threat Modeling
● Security Operations
● Log Analysis & Detection Packet Analysis
● Web Application Security
● Social Engineering
● Malware Analysis
● Threat Hunting
● Linux
● Windows

MODULE-03 (2 weeks)
Job Hunting
● Perfection Linkedin Profile
● Perfection Resume/ CV
● Mock Interviews
○ Behavioral Interviews
○ Technical Interviews

Eligibility:
● No 4-year degree required
● No previous coding experience required - really!

Targeted Job Title:
● Cyber Security Analyst
● Helpdesk Manager / Analyst
● Security Administrator
● Systems Administrator
● Security Engineer

Subjects:
Cyber Security, Systems Architecture, Entity Framework

Course Description:

In this course, participants will learn data types, data structure, and data lifecycle. Participants will gain a deep understanding and ability to derive insightful knowledge from raw data. This program focuses on the practical technical knowledge required to analyze and solve data problems in a meticulous and fast-paced way, it includes statistics basics, python libraries, pandas, NumPy, scipy, and stats, and diving into SQL, from designing to querying. Participants will learn how to analyze data to make better decisions and get a solid foundation in statistics to interpret the data better.
Program Flow:
● Data Analytics (13 Weeks)
Program Coverage:
● 210+ Hours In-class Training
● 60+ Hours Mentoring Service
● 10+ Assignments & Projects
● 3 Capstone Project
● CMS (Career Management Service) Support until First Hiring
Targeted Job Titles:
● Business Intelligence Analyst
● Data Analyst
● Tableau Developer
● Data Consultant
Eligibility: Candidates are supposed to have intermediate python programming knowledge and familiarity with fundamental IT issues such as Linux, Git/GitHub, and SQL Basics.

Subjects:
SciPy, NumPy, Python, Data Analytics, SQL, Statistics & Probability, Pandas

Course Description:

This program starts with a 6-week Prep for DS training specially prepared for those new to Data Analytics. With the guidance of your personal mentor and career coaches, you will graduate with an interview-ready portfolio and a network of Data Analysts/Scientists.
In this course, participants will learn data types, data structure, and data lifecycle. Participants will gain a deep understanding and ability to derive insightful knowledge from raw data. This program focuses on the practical technical knowledge required to analyze and solve data problems in a meticulous and fast-paced way, it includes statistics basics, python libraries, pandas, NumPy, scipy, and stats, and diving into SQL, from designing to querying. Participants will learn how to analyze data to make better decisions, get a solid foundation in statistics to interpret the data better, and prepare and share dashboards with this insight to stakeholders.
Program Flow:
● Prep for DS (6 Weeks)
● Data Analytics (19 Weeks)
Program Coverage:
● 250+ Hours In-class Training
● 45+ Hours Mentoring Service
● 50+ Hours Lab/Project Sessions
● 5+ Projects
● 1 Capstone Project
● CMS (Career Management Service) Support until First Hiring
Targeted Job Titles:
● Business Intelligence Analyst
● Tableau Developer
● Data Analyst
● Data Consultant
Eligibility:
● No 4-year degree required
● No previous coding experience required

Subjects:
NumPy, Python, Data Analytics, SQL

Course Description:

Learn how to
● Extract knowledge and insights from different data types,
● Use scientific methods, processes, algorithms, and systems in this interdisciplinary field and get the essential skills expected from a data scientist & ML Engineer.

Through this program, in addition to learning how to build complex quantitative algorithms and synthesize large amounts of information, gain the leadership and communication skills necessary to deliver measurable and tangible results to a variety of business stakeholders!

Program Flow:
● Preparatory Course (50+Hrs)
● Data Analytics (15 Weeks)
● Machine Learning & Deep Learning (15 Weeks)

Program Coverage:
● 350+ Hours In-class Training
● 45+ Hours Mentoring Service
● 80+ Hours Lab/Project Sessions
● 12+ Real Life Projects
● 4 Capstone Projects
● CMS (Career Management Service) Support until First Hiring

Targeted Job Titles:
● Business Intelligence Analyst
● Data Analyst
● Tableau Developer
● Data Scientist
● Machine Learning Engineer
● Data (Science) Consultant

Eligibility: Candidates are supposed to have intermediate python programming knowledge and familiarity with fundamental IT issues such as Linux it and SQL Basics.

Subjects:
Machine Learning, Data Analytics, Data Science

Course Description:

(This program starts with a 12-week IT Fundamentals (ITF) training specially prepared for those new to the IT sector or those needing significant skills building. You can skip this part if you are eligible. The duration of ITF is not added to the total duration.)
(After ITF), we deep dive into data science and machine learning fundamentals with Python. Throughout the course, you will gain a comprehensive understanding of the entire data science process from end to end, including data prep, data analysis, and visualization, as well as how to properly apply machine learning algorithms to various situations or tasks and model deployment on the cloud. This course was designed to prepare you for the real world. Each week, you’ll tackle interview-style questions and weekly exercises as you learn new topics to build the skills needed to land a new job as you learn the topics themselves.
What You’ll:
● Learn the end-to-end data science process, including data prep, data analysis, visualization, as well as use cases for both machine learning and deep learning algorithms
● Walk away with a work-applicable understanding of the Data Science process and how to use the methodologies and tools to solve real-world problems in business and academia.
● Learn how to retrieve and manipulate data using Python and SQL
● Learn how to prepare the dashboard that the business world needs on Tableau BI Tool ● Get an understanding of the importance of machine learning and the future growth of the industry
● Get a deep understanding of the strengths and weaknesses of different Machine Learning algorithms
● Learn how to deploy a model on the cloud systems such as AWS.
● Get a portfolio of projects to showcase to employers.
Program Flow:
● Data Analytics (13 Weeks)
● Machine Learning & Deep Learning (13 Weeks)
Program Coverage:
● 430+ Hours In-class Training
● 120+ Hours Mentoring Service
● 20+ Assignments & Projects
● 4 Capstone Projects
● CMS (Career Management Service) Support until First Hiring
Targeted Job Titles:
● Business Intelligence Analyst
● Data Analyst
● Tableau Developer
● Data Scientist
● Machine Learning Engineer
● Data (Science) Consultant
Eligibility:
● No 4-year degree required
● No previous coding experience required