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From Certification to Implementation: The First 90 Days on the Job

aws certified machine learning course,aws streaming solutions,aws technical essentials certification

From Certification to Implementation: The First 90 Days on the Job

Congratulations! You've successfully navigated the challenging world of AWS certifications and landed a new role. The ink on your certificates is still fresh, and you're filled with a mix of excitement and a healthy dose of "What now?" The transition from passing exams to delivering real-world value can feel daunting. This guide is designed to be your practical roadmap for the critical first 90 days. We'll break down this period into three manageable phases, showing you how to strategically apply the knowledge from your certifications—be it the foundational aws technical essentials certification, the specialized aws certified machine learning course, or expertise in aws streaming solutions—to establish yourself as a competent, proactive, and valuable team member from day one. The goal isn't to be an expert on everything immediately, but to build credibility, learn the specific context of your new environment, and translate your theoretical knowledge into tangible contributions.

Weeks 1-4: Apply Your Essentials Knowledge

Your first month is all about orientation and applying your broad, foundational understanding. This is where your AWS Technical Essentials Certification pays off immensely. Resist the urge to dive headfirst into complex projects. Instead, focus on comprehension and observation. Start by thoroughly understanding your company's specific AWS architecture. How are the VPCs structured? What naming conventions and tagging strategies are in place? Use the console and, if available, tools like AWS Cost Explorer and AWS Trusted Advisor—concepts you're familiar with from your Essentials studies—to get a lay of the land.

One of the most impactful ways to demonstrate immediate value is by becoming a security-conscious new hire. With your Essentials knowledge, you can conduct a careful review of IAM policies and roles. Look for overly permissive policies, unused IAM users, or roles with unnecessary privileges. Document your observations and discuss them with your mentor or team lead. This shows you're not just technically capable but also mindful of the shared responsibility model and security best practices. Similarly, keep an eye out for obvious cost optimization opportunities. Are there unattached EBS volumes, underutilized EC2 instances, or old S3 object versions? Presenting a well-researched, small list of potential savings during your first few weeks is a fantastic way to prove your attentiveness and business acumen. Remember, the goal here is to listen, learn the internal processes, and use your certified foundational knowledge to ask intelligent questions and spot low-hanging fruit that others might have overlooked.

Weeks 5-8: Contribute to a Specialized Project

By your second month, you should be comfortable with the team's rhythm and basic workflows. Now it's time to lean into your specialized certification knowledge. This is the phase where you move from general observation to targeted contribution. Proactively volunteer for tasks that align with your advanced skills. If you have deep knowledge of AWS Streaming Solutions, express your interest in the team's real-time data infrastructure. Ask if you can help troubleshoot a minor issue in a Kinesis Data Streams pipeline, assist in documenting the flow of data from producers to consumers, or write a small script to monitor the health of a Firehose delivery stream. Your theoretical understanding of concepts like shards, partition keys, and consumer applications becomes practical here.

Alternatively, if your specialization came from an AWS Certified Machine Learning course, seek out the data science or MLOps team. Don't ask to build a new model right away. Instead, offer to help with the operational side. You could volunteer to review the performance metrics and drift of an existing SageMaker endpoint in production, help clean or label a batch of data for an upcoming training cycle, or automate the deployment of a model using SageMaker Pipelines. This demonstrates humility, a willingness to learn the existing stack, and a practical application of your ML lifecycle knowledge. The key in this phase is to find a small, well-scoped ticket or task where you can apply your specialized certification knowledge, deliver a clear result, and, most importantly, learn from the experienced engineers on your team. It bridges the gap between your individual certification journey and the team's collective goals.

Weeks 9-12: Propose a Small Improvement

As you approach the end of your first 90 days, you have a unique perspective: you possess fresh certification knowledge and a growing understanding of your company's specific technical landscape. Now, synthesize these two strengths. Your mission for this final phase is to propose and, ideally, begin a small proof-of-concept (PoC) that demonstrates initiative and combined skill value. Think about how you can connect the dots between different areas of your expertise.

For example, if you worked with both foundational services and AWS Streaming Solutions, you might propose a PoC for a real-time log alerting system. You could design a flow where CloudWatch Logs are streamed via Kinesis Data Firehose, processed with a Lambda function for anomaly detection, and then trigger alerts in Slack or PagerDuty. This showcases your ability to build integrated, event-driven solutions. On the other hand, if your path included the AWS Certified Machine Learning course alongside your core AWS knowledge, you could identify a manual, repetitive task—like categorizing support tickets or resizing uploaded images—and propose a simple automated solution using Amazon Rekognition, Comprehend, or a custom Lambda function invoking a SageMaker endpoint. Draft a one-page document outlining the problem, your proposed AWS architecture, a rough estimate of cost and effort, and the expected benefit. Present this to your manager not as a demand, but as a thoughtful suggestion for a valuable experiment. This final step transforms you from a certified learner into a proactive problem-solver who can envision and articulate how AWS technologies create practical business value, setting a strong foundation for your long-term growth and impact within the organization.