Achievements & Certifications

Successfully completed the "Knowledge Check: Get Started with Databricks for Data Engineering" course, gaining hands-on experience with Databricks and its ecosystem for data engineering workflows. The course provided practical insights into handling large-scale data, optimising data pipelines, and leveraging cloud-based analytics.

Key Learnings:

• Explored Apache Spark fundamentals, enhancing my ability to process large datasets efficiently.

• Developed data pipelines in Databricks, focusing on ETL processes and data transformation.

• Gained experience in Delta Lake, improving data reliability and consistency in big data environments.

• Implemented structured streaming for real-time data processing and analytics.

• Strengthened proficiency in SQL, Python, and Spark within Databricks for scalable data engineering solutions.

• Improved ability to design and optimise distributed computing workflows for large-scale data analytics.

Completed a practical job simulation focusing on delivering actionable insights and strategic recommendations for client-facing scenarios in the telecom industry. This immersive experience provided the opportunity to analyse complex datasets and create dynamic Power BI dashboards to inform business decision-making and client engagement strategies.

Key Learnings:​

• Analysed customer retention data to identify high-risk customers, uncovering patterns and trends that informed proactive retention strategies.

• Conducted in-depth HR data analysis to explore gender-related KPIs, pinpointing root causes of executive-level gender imbalances and recommending solutions.

• Delivered clear and concise email communication to engagement partners, providing data-driven insights and actionable recommendations.

• Enhanced expertise in data visualisation and storytelling, ensuring insights were self-explanatory and tailored for executive decision-making.

• Strengthened problem-solving and critical-thinking skills, applying analytics to tackle real-world business challenges and propose strategic initiatives.

Completed a real-world data analytics simulation with a focus on delivering commercial insights and strategic recommendations for the data science team. This hands-on experience provided an opportunity to work with transaction datasets, enhancing my data preparation, customer analytics, and reporting skills to support business decision-making effectively.

Key Learnings:

• Utilised transaction datasets to extract valuable insights, identifying patterns and trends to support data-driven commercial recommendations.

• Applied analytical techniques to identify benchmark stores and conducted uplift testing for trial store layouts, enabling evidence-based decision-making.

• Created comprehensive reports for the Category Manager, leveraging advanced data analytics to inform strategic decisions.

• Enhanced skills in customer analytics, data preparation, and visual communication of insights to drive impactful business strategies.

• Gained practical experience in delivering commercial applications of analytics to support category management and business growth.

Simulated a real-world data science challenge at British Airways, analysing customer review data and building a predictive model to identify factors influencing purchasing behaviour. The project enhanced my Python skills (Jupyter Notebook) and helped me translate data insights into actionable business outcomes. I also developed strong communication skills by presenting findings in a business context using PowerPoint.

Key Learnings:

• Scraped and analysed customer review data for insights.

• Built and fine-tuned a predictive model for buying behavior.

• Strengthened Python (Jupyter Notebook) and data analysis skills.

• Improved communication by presenting technical results clearly.

• Gained insight into applying data science in the airline industry.

• Acquired proficient command of Excel functionalities and data analysis techniques, including data cleansing, and manipulation, and conditional formatting techniques.

• Acquired proficiency in automation by learning to record macros and script in Visual Basic for Applications (VBA), developing two functional macros integrated with buttons using account sales data.

• Gained expertise in data visualisation and storytelling using Excel and PowerPoint by creating impactful charts and interactive dashboards.

I recently completed the "Introduction to Tools and Techniques in Data Science" course offered by IBM. This course provided a comprehensive overview of essential tools and technologies used in data science, including Jupyter Notebook, Docker, SQL, and various virtual environments. Through hands-on exercises and real-world applications, I gained practical experience in utilizing these tools to efficiently manage, analyze, and visualize data, equipping me with a solid foundation for advanced data science projects.

Learning objectives

• Apply the required hardware to successfully run Power BI.

• Distinguish between different data types in Power BI.

• Correlate the similarities between visualizations in Power BI.

• Identify the outcomes when changes are made within Power BI and Power BI Desktop.

• Differentiate between dashboards and reports within Power BI.

• Determine user roles within a workspace in Power BI.

• Manage workspaces and tools within the Power BI mobile application.

This course has equipped me with a comprehensive understanding of machine learning using Scikit-Learn. I've mastered essential concepts like classification, regression, and clustering, gaining practical skills in building and evaluating machine learning models. Additionally, I've learned to leverage Python libraries effectively for data analysis and model implementation. 

Completed a course and a quiz which included all the regulations and norms related to data and data protection. This course also included information about cyber security. 

This course is meticulously designed to provide a comprehensive understanding of Data Analytics, ensuring a solid foundation in both theoretical and practical aspects of the field. It encompasses all core concepts of Data Analysis, equipping learners with essential skills to excel in data-driven environments. Through hands-on exercises and case studies, participants gain invaluable experience in interpreting data, deriving actionable insights, and applying analytical techniques to drive decision-making across diverse industries.

As a Community Manager at Harmony, I play a pivotal role in building and sustaining an active and inclusive community of developers and contributors. My responsibilities encompass a wide range of activities aimed at fostering collaboration, maintaining quality, and driving engagement:

• GitHub Management: Reviewing pull requests, overseeing code contributions, and creating detailed, actionable issues to guide development.

• Streamlining Code Reviews: Enhancing processes to maintain quality and encourage productive collaboration.

• Discord Community Engagement: Facilitating discussions, addressing queries, and directing community members to relevant resources.

• Promoting Developer Outreach and Coding Challenges: Designing and promoting coding challenges to connect with and engage diverse developer communities.

• Fostering an Inclusive Culture:Building an open and collaborative environment aligned with Harmony’s mission and values.

As a Community Member of AICamp, I actively engage in a dynamic and collaborative environment focused on learning and practising cutting-edge AI technologies, including Generative AI, LLMs, ChatGPT, Machine Learning, Deep Learning, MLOps, and Data Engineering.

AICamp serves as a hub for AI enthusiasts across London, fostering a community where developers and professionals come together to explore the latest advancements through tech talks, hands-on workshops, and code labs. The organisation regularly hosts industry leaders from innovative companies and successful startups to share their real-world experiences and practices, providing invaluable insights into the ever-evolving world of AI.

Being part of this community allows me to deepen my understanding of AI and Data technologies, network with like-minded professionals, and contribute to meaningful discussions on AI's transformative potential.

Learn more about AICamp: https://www.aicamp.ai

Simulated real-world data science projects using SQL, Tableau, Python, and Spark, enhancing my ability to handle diverse datasets and derive actionable insights. The course provided hands-on experience across different platforms, strengthening my technical proficiency and analytical skills. I also gained valuable experience in presenting data-driven solutions effectively using visualisations and dashboards.

Key Learnings:

• Analyzed employee data using SQL to extract meaningful insights.

• Developed an interactive sales dashboard in Tableau to showcase key performance metrics.

• Conducted in-depth sales analysis with Python, focusing on data preprocessing and statistical analysis.

• Utilised Apache Spark for large-scale service analysis, showcasing expertise in big data processing.

• Strengthened Python, SQL, and Tableau skills while gaining hands-on experience with Spark.

• Enhanced communication skills by presenting complex findings clearly through visualizations.

As a proud member of The British Computer Society (BCS), I am committed to upholding the highest standards in the field of computing and information technology. My membership with BCS reflects my dedication to continuous professional development and my engagement with the latest industry practices and innovations. This affiliation supports my commitment to delivering excellence and contributing to the advancement of technology in meaningful ways.

I'm thrilled to announce the completion of my new course- Best Practices of Data Warehousing with Amazon Redshift - AWS. This course provided me with a deep understanding of optimizing data warehousing solutions using Amazon Redshift. I learned how to design scalable and efficient data architectures, enhance query performance through best practices, and implement effective data management strategies. Key takeaways include advanced techniques for data distribution and sorting, strategies for maintaining performance with large datasets, and methods for cost-effective data storage and retrieval. With these insights, I'm well-prepared to leverage Redshift's powerful features to drive data-driven decision-making and improve overall data efficiency.

Completed a job simulation involving AI-powered financial chatbot development for BCG's GenAI Consulting team.

• Gained experience in Python programming, including the use of libraries such as pandas for data manipulation.

• Integrated and interpreted complex financial data from 10-K and 10-Q reports, employing rule-based logic to create a chatbot that provides user-friendly financial insights and analysis.

• Implemented machine learning models to enhance the chatbot's ability to predict financial trends and offer personalized recommendations based on user input and historical data.

I've completed a comprehensive course diving into the core principles of data engineering, equipping me with essential skills in data processing, storage, and management. From mastering ETL pipelines to understanding data warehouses and cloud computing, I'm now prepared to harness the power of data effectively.

This course consists of all the basics and essential about data protection. GDPR(General Data Protection Regulations) was also included in this course.

getCredible is First Talent Referral Platform. In this role I gained experience in marketing the getCredible App. Assisted students in understanding platform functionality. Created regular reports & feedback for continuous improvement. Participated in various Networking events.