Full Stack AWS Cloud Computing Career Path
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About This Course
What You'll Learn
Core AWS Skills You Will Learn
- Proficiency in setting up and managing core AWS services like EC2, S3, and RDS.
- Understanding the principles of cloud computing, including on-demand resource availability and pay-as-you-go pricing.
- Skills to create and secure AWS accounts and manage access through IAM policies.
- Ability to design and implement robust cloud infrastructure using VPC, subnets, and route tables.
- Knowledge of managing data storage solutions with AWS services like S3, EBS, and Glacier.
- Capability to deploy and manage applications using AWS compute services, including EC2, Lambda, and ECS.
Tools and Technologies You Will Learn
- AWS EC2: Virtual servers for running applications.
- AWS S3: Scalable storage for data and media files.
- AWS RDS: Managed relational database services.
- AWS VPC: Virtual Private Cloud for secure networking.
- AWS Lambda: Serverless computing to run code without managing servers.
- AWS CloudWatch: Monitoring and logging service for tracking application performance.
- AWS CloudFormation: Infrastructure as code for automating resource management.
- AWS IAM: Identity and Access Management for securing AWS resources.
- AWS Route 53: DNS service for high availability and scalability.
- AWS CloudTrail: Service for logging and monitoring AWS API activity.
- AWS DynamoDB: Managed NoSQL database service for fast and flexible data retrieval.
Essential communication and business skills relevant to the cloud computing domain:
- Stakeholder Communication: Clearly explain cloud computing solutions, benefits, and potential challenges to stakeholders, ensuring alignment with business goals and IT strategies
- Technical Documentation: Create comprehensive and accessible documentation for cloud architectures, services, and implementation processes to facilitate understanding and collaboration among team members.
- Project Management: Plan, coordinate, and oversee cloud computing projects efficiently, ensuring timely delivery, budget adherence, and alignment with organizational objectives.
- Cost-Benefit Analysis: Present detailed analyses of cloud service costs and benefits to non-technical stakeholders, aiding in informed decision-making and budget planning
- Cross-Functional Collaboration: Work effectively with IT, security, and business teams to integrate cloud solutions seamlessly into the company's operations and infrastructure.
Business Problem Solving using AWS
- Analyze and define business needs to align AWS solutions with organizational goals.
- Design cloud architectures that scale with demand using AWS services like EC2, Auto Scaling, and Load Balancer.
- Implement strategies to optimize cost-efficiency and performance using AWS Cost Explorer and performance monitoring tools.
- Develop secure and compliant cloud solutions by leveraging AWS IAM, Security Groups, and compliance services.
- Apply design thinking principles to create innovative and user-centric AWS solutions.
- Design and implement robust disaster recovery and high-availability strategies using AWS services like Route 53, CloudFront, and Backup.
Curriculum Designed For Career Success
Module 1: Introduction to AWS Cloud Computing
3 Lectures
Gain a foundational understanding of AWS Cloud Computing and its applications across various industries. This module will help you understand how businesses like Netflix and Airbnb leverage AWS for scalable, cost-effective, and high-performing infrastructure. For example, a startup wanting to avoid large upfront costs can use AWS to deploy applications quickly and scale as needed without investing in physical hardware.
- 1.1 Overview of AWS services and architecture:
- Understand the comprehensive suite of AWS services and how they integrate to form a robust cloud architecture. Real-world application: An online retailer can use AWS services like EC2 for hosting their website, S3 for storing product images, and RDS for managing customer orders.
- 1.2 Understanding the cloud computing paradigm:
- Learn the principles of cloud computing including on-demand resource availability and pay-as-you-go pricing. Real-world application: A startup can scale their infrastructure as they grow, paying only for the resources they use, thus minimizing upfront costs.
- 1.3 Benefits and use cases of AWS in various industries:
- Explore how AWS is utilized across different sectors. Real-world application: In healthcare, AWS can manage large datasets of patient records with high security and compliance with regulations like HIPAA.
Module 2: AWS Fundamentals and Core Services
2 Lectures
Learn the core AWS services essential for setting up a basic cloud environment. Understand how businesses use services like EC2 for computing power, S3 for storage, and RDS for databases to handle everyday operations. An e-commerce company, for instance, can use S3 for storing product images and videos, EC2 instances to run their website, and RDS to manage their customer database efficiently.
- 1.1 Introduction to core AWS services (EC2, S3, RDS, etc.):
- Get familiar with essential AWS services. Real-world application: A fintech company can use EC2 instances to run their applications, S3 to store transaction logs, and RDS for maintaining their customer databases.
- 1.2 Setting up AWS accounts and managing security::
- Learn to create and secure AWS accounts. Real-world application: An organization can manage multiple AWS accounts for different departments, ensuring secure access through IAM policies.
- Learn to create and secure AWS accounts. Real-world application: An organization can manage multiple AWS accounts for different departments, ensuring secure access through IAM policies.
Module 3: Cloud Infrastructure and Networking
3 Lectures
Design robust cloud infrastructure to ensure high availability and security. Networking in AWS enables businesses to connect their applications and services securely. For example, a multinational corporation can set up a Virtual Private Cloud (VPC) to isolate its sensitive data and use Subnets to organize resources across different geographical regions for optimal performance and compliance with local regulations
- 1.1 Designing and implementing cloud infrastructure:
- Plan and build scalable cloud environments. Real-world application: A multinational company can design a global infrastructure with VPCs and subnets to ensure efficient and secure communication between their worldwide offices.
- 1.2 Networking concepts in AWS (VPC, Subnets, Route Tables):
- Understand the networking aspects of AWS. Real-world application: An enterprise can set up VPCs to isolate sensitive financial data, ensuring it is only accessible by authorized systems.
- 1.3 Optimizing network performance and security:
- Techniques to enhance network efficiency. Real-world application: An e-commerce platform can use Route 53 to route users to the nearest data center, improving load times and user experience.
Module 4: Storage and Database Services
3 Lectures
Efficiently manage and store large volumes of data using AWS storage solutions. Learn how a media company can use S3 for storing vast amounts of video content, Glacier for long-term archival storage, and RDS to manage metadata about their content library.
- 1.1 Understanding AWS storage options (S3, EBS, Glacier):
- Learn about different AWS storage solutions. Real-world application: A media company can use S3 for storing video content, EBS for high-performance storage attached to EC2, and Glacier for archiving older footage.
- 1.2 Introduction to AWS database services (RDS, DynamoDB):
- Overview of AWS database offerings. Real-world application: A gaming company can use DynamoDB for high-speed data retrieval in gaming applications, ensuring a seamless player experience.
- 1.3 Best practices for data storage and management in AWS:
- Learn effective data management strategies. Real-world application: A financial institution can implement robust data backup and disaster recovery plans using S3 and Glacier.
Module 5: Compute Services and Serverless Computing
3 Lectures
Deploy and scale applications efficiently without managing underlying infrastructure. Understand how a financial services company can use AWS Lambda to execute transaction processing without managing servers, reducing operational overhead and improving scalability.
- 1.1 Exploring AWS compute services (EC2, Lambda, ECS):
- Dive into AWS compute capabilities. Real-world application: An AI startup can use EC2 for high-performance computing tasks, ECS for container management, and Lambda for running microservices without server management.
- 1.2 Serverless computing with AWS Lambda:
- Build applications without managing servers. Real-world application: A payment processing company can use Lambda to execute code in response to transaction events, improving scalability and reducing costs.
- 1.3 Building and deploying serverless applications:
- Practical serverless application development. Real-world application: An IoT company can deploy serverless applications that process data from thousands of devices in real-time.
Module 6: Scalability and High Availability
3 Lectures
Ensure applications can scale and remain available during peak times, crucial for customer satisfaction and business continuity. For instance, a retail company experiencing high traffic during Black Friday can use AWS Auto Scaling to handle traffic spikes and Route 53 for DNS management to ensure their website remains accessible.
- 1.1 Scaling applications on AWS using auto-scaling and load balancing:
- Ensure applications can handle varying loads. Real-world application: A social media platform can use auto-scaling to manage user spikes during peak times and load balancers to distribute traffic efficiently.
- 1.2 Achieving high availability with AWS services (Route 53, CloudFront):
- Maintain application uptime and performance. Real-world application: A global streaming service can use Route 53 for DNS failover and CloudFront for content delivery, ensuring a smooth viewing experience.
- 1.3 Disaster recovery and backup strategies in AWS:
- Plan for data protection and recovery. Real-world application: A law firm can implement automated backups and disaster recovery plans to protect sensitive client data.
Module 7: Security and Compliance
3 Lectures
Implement robust security measures to protect sensitive data and ensure compliance with regulations. Learn how a healthcare provider can use IAM for access control, Security Groups to manage traffic, and encryption to secure patient data, ensuring compliance with HIPAA regulations.
- 1.1 Securing AWS resources with IAM, Security Groups, and ACLs:
- Implement robust security measures. Real-world application: A healthcare provider can use IAM to control user access, Security Groups to define traffic rules, and ACLs to add an additional layer of security.
- 1.2 Compliance and governance in AWS:
- Ensure adherence to industry regulations. Real-world application: A financial institution can use AWS compliance tools to meet regulatory requirements like GDPR and PCI-DSS.
- 1.3 Implementing encryption and data protection measures:
- Protect data at rest and in transit. Real-world application: An online banking service can use encryption to secure customer data, ensuring privacy and security.
Module 8: Monitoring and Optimization
3 Lectures
Maintain performance and optimize costs through monitoring AWS environments. Understand how an online service provider can use CloudWatch to monitor application performance, CloudTrail to log API activity for auditing purposes, and Cost Explorer to analyze and optimize AWS spending.
- 1.1 Monitoring AWS resources with CloudWatch and CloudTrail:
- Track and log AWS resource usage. Real-world application: An IT department can use CloudWatch for performance monitoring and CloudTrail for auditing API calls, ensuring operational transparency and security.
- 1.2 Performance optimization techniques::
- Enhance the efficiency of AWS deployments. Real-world application: An e-commerce site can optimize their database queries and application code to reduce latency and improve response times.
- 1.3 Cost management and billing in AWS:
- Manage and optimize AWS spending. Real-world application: A startup can use AWS Cost Explorer to monitor and control their cloud expenses, ensuring they stay within budget.
- Manage and optimize AWS spending. Real-world application: A startup can use AWS Cost Explorer to monitor and control their cloud expenses, ensuring they stay within budget.
Case Studies
Industry Case Studies You Will Work On
Risk Assessment with Deep Learning
Predict the likelihood of credit default for loan applicants, helping risk analysts and credit officers improve loan approval processes and reduce default rates.
Skills learned:
Data Preprocessing
Feature Engineering
Model Evaluation
Customer Behavior Analysis
Analyze customer behavior patterns to predict future actions, such as account closure or product churn, enabling targeted strategies for customer retention.
Skills learned:
Sequential Data Processing
Time Series Analysis
Predictive Modeling
Fraud Detection Using Deep Learning
Detect fraudulent transactions in real time by analyzing transaction data patterns, improving fraud detection capabilities and reducing financial losses.
Skills learned:
Anomaly Detection Techniques
Feature Extraction
Model Evaluation
Customer Sentiment Analysis
Analyze customer sentiments from feedback data to gauge satisfaction levels, helping teams identify areas for improvement in banking services.
Skills learned:
Natural Language Processing (NLP)
Sentiment Analysis Techniques
Chatbot Development for Customer Service
Develop AI-powered chatbots to handle customer inquiries and provide instant assistance, improving customer experience and service efficiency.
Skills learned:
Natural Language Processing (NLP)
Conversational AI
Model Deployment
Investment Portfolio Optimization
Optimize investment portfolios by predicting asset performance and rebalancing strategies, helping wealth managers enhance returns and manage risks effectively.
Skills learned:
Time Series Analysis
Predictive Modeling
Portfolio Optimization Techniques
Loan Approval Automation
Develop an automated system to assess loan applications, reducing manual intervention and accelerating loan processing for improved efficiency.pre
Skills learned:
Predictive Modeling
Risk Assessment Techniques
Model Deployment
Predictive Pricing Models
Develop predictive models to forecast pricing trends and optimize strategies, enabling pricing teams to align product pricing with market dynamics.
Skills learned:
Time Series Analysis
Predictive Modeling
Pricing Analytics
Predictive Lending Models
Develop personalized lending models to offer tailored loan products, helping credit departments improve customer satisfaction and portfolio performance.
Skills learned:
Predictive Modeling
Customer Segmentation
Personalized Recommendation Systems
Network Intrusion Detection
Detect and prevent cyberattacks by analyzing network traffic patterns, strengthening cybersecurity measures and protecting sensitive banking data.
Skills learned:
Intrusion Detection Techniques
Anomaly Detection
Cybersecurity Fundamentals
Advanced Fraud Detection Techniques in Banking
Learn the skills and knowledge to detect fraudulent activities in credit card transactions, ensuring financial security and reducing losses from fraud.
Skills learned:
Data Preprocessing
Feature Engineering
Model Evaluation
Anomaly Detection Techniques
Customer Segmentation Strategies
Learn how to segment customers based on their behavior and demographics to optimize marketing campaigns for targeted engagement and retention.
Skills learned:
Data Visualization
Clustering Algorithms
Customer Profiling techniques
Operational Efficiency Optimization
Develop tools and techniques to forecast call volumes in customer service centers, improving resource allocation and enhancing service efficiency.
Skills learned:
Time Series Analysis
Model Evaluation
Operational Optimization Techniques
Sales Prediction and Optimization
Learn how to predict sales performance and optimize strategies for products and services to drive revenue growth and customer acquisition.
Skills learned:
Predictive Modeling
Sales forecasting
Model Interpretation Techniques
Real-Time Fraud Detection
Equip yourself with the skills to detect fraudulent activities in real-time transactions, safeguarding organizations from financial losses.
Skills learned:
Data Preprocessing
Pattern Recognition
Anomaly Detection Techniques
Predictive Modeling for Risk Assessment
Predict default probabilities to assess risk and make informed decisions, helping organizations manage portfolios more effectively.
Skills learned:
Feature Engineering
Risk Assessment
Model Evaluation Techniques
Predictive Analytics for Customer Lifetime Value Estimation
Learn how to estimate the lifetime value of customers, enabling personalized marketing strategies and enhancing customer experiences.
Skills learned:
Customer Segmentation
Predictive Modeling
Customer Lifetime value calculation techniques
Personalized Cross-Selling Recommendations
Gain the skills to build recommendation systems for cross-selling products and services based on customer behavior and preferences.
Skills learned:
Collaborative Filtering
Recommendation Algorithms
Customer Profiling techniques
Machine Learning for Risk Assessment
Learn the tools to assess risks in decision-making processes, enabling better strategies and management for large-scale operations.
Skills learned:
Feature Selection
Risk Modeling
Credit Scoring Techniques
Automated CI/CD Pipeline for ML Models
Develop an automated CI/CD pipeline to streamline the deployment of machine learning models, ensuring quick and reliable integration into production environments.
Skills learned:
Pipeline Design
Automated Testing
Continuous Deployment
Real-Time Model Monitoring and Drift Detection
Set up real-time monitoring systems to track ML model performance and detect model drift, ensuring accuracy and reliability in changing environments.
Skills learned:
Performance Monitoring
Drift Detection
Metric Logging
Scalable Model Deployment with Docker and Kubernetes
Learn to containerize ML models using Docker and deploy them at scale with Kubernetes for reliable, efficient, and reproducible production environments.
Skills learned:
Containerization
Orchestration
Scalable Deployment
Data Versioning and Governance Framework
Design a robust data versioning and governance framework to ensure reproducibility, data integrity, and compliance with industry regulations.
Skills learned:
Data Version Control
Compliance
Governance Frameworks
Hyperparameter Tuning for Model Optimization
Implement hyperparameter tuning techniques to improve the performance of ML models, ensuring they meet production requirements effectively.
Skills learned:
Hyperparameter Tuning
Experiment Tracking
Model Optimization
End-to-End Workflow with TensorFlow Extended (TFX)
Build an end-to-end ML pipeline using TensorFlow Extended (TFX), including data ingestion, preprocessing, model training, and deployment.
Skills learned:
Pipeline Construction
Data Preprocessing
Model Deployment
Implementing Monitoring for Ethical AI Compliance
Design monitoring systems to ensure ML models align with ethical AI practices, addressing issues such as bias detection and fairness.
Skills learned:
Bias Detection
Fairness Metrics
Ethical AI Monitoring
Multi-Model Deployment and Load Balancing
Deploy multiple machine learning models in production and implement load balancing strategies to ensure efficient resource utilization and response times.
Skills learned:
Multi-Model Serving
Load Balancing
Resource Optimization
Image Enhancement and Filtering
Learn to enhance image quality using basic image processing techniques like blurring, sharpening, and edge detection. This foundational skill is crucial for preparing images for further analysis.
Skills learned:
Image filtering
edge detection
blurring
sharpening
Basic Object Detection in Images
Understand how to detect objects within images using bounding boxes and simple detection algorithms. Lay the groundwork for developing systems that can identify objects in various scenarios.
Skills learned:
Object detection
bounding box creation
using detection algorithms
Image Classification of Everyday Objects
Train a simple CNN to classify images into categories like animals, vehicles, or everyday items. This project introduces you to deep learning concepts and how they’re applied in image classification.
Skills learned:
Image classification
CNN basics
training deep learning models
Face Detection in Photos
Learn to detect faces in photos using algorithms like Haar cascades. This hands-on project provides a foundation in object detection and recognition systems.
Skills learned:
Face detection
Feature recognition
Algorithm implementation
Panorama Stitching
Combine multiple images to create seamless panoramic views using keypoint detection, feature matching, and image alignment techniques.
Skills learned:
Keypoint detection
Feature matching
Image stitching
Tracking Moving Objects in Videos
Track objects like moving balls or people in a video sequence using basic tracking algorithms. This project introduces the essentials of object tracking and algorithm implementation.
Skills learned:
Object tracking
Video analysis
Tracking algorithm implementation
Color-Based Image Segmentation
Segment images into meaningful regions by identifying specific colors and grouping similar pixels. Learn how segmentation techniques are used in organizing image content.
Skills learned:
Image segmentation
Color detection
Pixel classification
Edge Detection for Shape Identification
Detect edges in images to identify shapes and structures. This project focuses on preprocessing techniques that lay the foundation for more advanced computer vision tasks.
Skills learned:
edge detection
shape identification
Preprocessing techniques
Make A Life-Changing Career Choice
IN-DEMAND CAREER
45%
Growth in demand for Data Scientists in the next 5 years
MASSIVE JOB OPENINGS
1M +
Job openings and counting for Data Scientists worldwide.
BIGGEST GROWING INDUSTRY
$349.6 Billion
Amount industry is set to grow by 2030
HIGH ENTRY- LEVEL SALARY
₹8-14 LPA+
Current average CTC for entry-level Data Scientists in India.
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Is This Course Right For You?
Are you looking for a career change?
Do you want to switch from your current job to a more rewarding and in-demand career?
Do you want a promotion?
Are you a working professional looking to upgrade your career with the most sought after skill in today’s job market?
Are you a beginner to data science?
Are you a complete beginner to data science with no coding background who’s looking for a comprehensive program that teaches you everything you need to know from scratch?
If you answered ‘Yes’ to any of the above, SkillCamper’s Full Stack Career Path is the perfect fit for you!
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Capstone projects
Live Classes
Flexible study options
Cancel anytime in first 7 days, full refund
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15+ hours of sessions with industry veterans & experts
Personalized mentorship by course instructors
Unlimited 1:1 doubt solving sessions
Career Support
Personalized placement assistance
1:1 mock interviews with industry experts
Soft-skills training module
Essential digital tools for digital workplace module
Interview preparation module
Masterclass on resume building & LinkedIn
Access to curated companies & jobs
Frequently Asked Questions
What technologies will I learn in the AWS Cloud Computing Bootcamp?
You’ll learn the core services of Amazon Web Services (AWS), such as EC2 for cloud computing, S3 for storage, and RDS for databases. The bootcamp covers key cloud computing concepts like networking, security, and deployment, giving you practical experience in building and managing cloud infrastructure.
Is this bootcamp suitable for beginners with no cloud computing experience?
Yes, this bootcamp is designed specifically for beginners. You don’t need any prior knowledge of cloud computing, and we’ll start with the basics to help you build a strong foundation as you progress toward advanced AWS topics.
How long does the AWS Cloud Computing Bootcamp take, and can I learn at my own pace?
The bootcamp runs for 4 months, and you can choose to follow a flexible schedule. You can learn at your own pace with self-guided modules or join live classes with industry experts. The bootcamp is designed for working professionals, with a time commitment of about 15–20 hours per week.
What will I learn during the bootcamp?
You’ll learn how to design, deploy, and manage cloud-based solutions using AWS services. Topics include compute services, storage solutions, networking, serverless computing, security best practices, and scalability. By the end, you’ll be prepared to take AWS certification exams and apply your skills in real-world cloud environments.
Can I access the course materials after completing the bootcamp?
Yes, you will have lifetime access to all course materials, recorded sessions, and project files. This allows you to revisit content and continue learning even after the bootcamp has ended.
What kind of career support is available during and after the bootcamp?
You’ll receive personalised career support, including 1:1 mentorship, mock interviews with cloud professionals, and resume-building assistance. We also provide access to our network of hiring partners, helping you connect with potential employers and job opportunities in the cloud computing field.
What makes this AWS Bootcamp different from other courses?
This bootcamp emphasises real-world projects, hands-on learning, and industry-tested problem-solving frameworks. You’ll get 1:1 mentorship and have the flexibility to choose between live or self-paced learning. We also offer a 7-day money-back guarantee, so you can explore the program risk-free.
How much does the bootcamp cost, and are there flexible payment options?
The bootcamp costs ₹75,000, and we offer easy EMI plans to make the course more accessible. Plus, you can try the program with our 7-day no-questions-asked money-back guarantee to ensure it’s the right fit for you.
What kinds of projects will I work on during the bootcamp?
You’ll work on practical projects that involve building and managing AWS infrastructure, such as deploying secure and scalable cloud solutions, optimising resources, and implementing serverless computing. These projects will help you apply your knowledge to real-world cloud challenges.
How will this bootcamp help me start a career in cloud computing?
By the end of the bootcamp, you’ll have a portfolio of cloud-based projects that demonstrate your expertise in AWS. With our career support and 1:1 mentorship, you’ll be prepared for job interviews, and we’ll help you connect with potential employers in the fast-growing cloud computing industry.
I don’t have a tech background; can I still take this course?
Yes, this bootcamp is designed for beginners. We start from foundational concepts, so prior experience isn’t necessary.
What type of job support do you provide after completing the course?
We offer comprehensive placement assistance, including resume building, mock interviews, and leveraging our network of industry partners.
How do you prepare students for the job market?
We equip students with industry-relevant skills, help craft winning resumes, and provide mock interview practice with experienced mentors.
Do you guarantee a job after completing the course?
While we do not guarantee a job, we provide extensive support to help you become highly competitive in the job market.
Can you help me find a job in any specific industry?
Our job assistance is generalized; we prepare you for a variety of roles in the data science field rather than focusing on specific industries.
What is the cost of the Data Science bootcamp?
The cost varies depending on the program. Our full bootcamp is priced between ₹50,000 and ₹75,000, depending on whether you choose self-paced or live instruction.
Are scholarships available for the courses?
Yes, we offer scholarships that can cover up to 70% of the tuition fees, making our courses more accessible to a wider range of students.
What is included in the course fee?
The fee includes access to all course materials, live coding sessions, AI-based learning platform, case studies, capstone projects, and mentorship from industry experts.
What payment options are available for the course fees?
We offer flexible payment options, including easy EMIs, and you can cancel anytime in the first 7 days for a full refund.
Is financial aid or other support available aside from scholarships?
While our primary financial support is through scholarships, our enrollment advisors can also assist you with payment plans and financing options to help manage the cost of your education.
Ready to become a Data Scientist that industry loves to hire? Apply Now.
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