Numan Anjum Data Scientist, Data Engineer, Data Analyst,Python
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Unveiling the Potential of Data Science: Your Pathway to Success
Greetings, eager learners! I am Numan Anjum, a dedicated Full Stack Data Scientist committed to not just teaching but guiding you through the complicated domains of Data Science, Machine Learning, and Artificial Intelligence.
Embarking on a journey in Data Science is like setting sail in an ocean of opportunities. It’s not just a career; it's a dynamic, ever-evolving expedition that demands both proficiency and vision. As a mentor, I am not merely an instructor but a navigator, steering you through the world of data analysis and interpretation.

Mapping Your Journey
Starting in Data Science can be daunting; the field consists of numerous technologies and methodologies. Fear not! I am here, to illuminate the path towards a comprehensive understanding of the field. From fundamental data analysis techniques and mastering Microsoft Excel, SQL, and Python, to harnessing the power of visualization tools like Power BI or Tableau for impactful reporting, your foundational steps will be solidified under my guidance.

Navigating the Terrain
As we progress, we delve into the more intricate territories. We'll explore the complexities of big data processing using Hadoop and Spark, understanding cloud ecosystems like Microsoft Azure, navigating platforms such as Databricks and Data Factory, and harnessing the potential of data warehouses and lakes. Together, we'll bridge the gap between Data Science and Data Engineering, delving into analytics, creating robust pipelines, and engineering solutions that solve real-world problems.

The Complete Lifecycle
Data Science isn’t just about coding; it's about understanding the complete lifecycle. I'll equip you with the skills to gather, clean, process, analyze, and visualize data, transforming raw information into actionable insights. Beyond technical proficiency, we’ll focus on developing your problem-solving skills and fostering a mindset that thrives on innovation.

Crafting Your Future
As we navigate this intricate landscape, my goal is not only to make you proficient but to empower you to create your future. Whether you aim to be a data analyst, data or ML engineer, scientist, or architect, I'll provide guidance on carving your unique path in this diverse field. I believe in nurturing not just skilled practitioners, but visionary leaders who shape the future of data-driven innovation.

Embark on the Journey
Take that crucial step forward and join me on this transformative expedition. From mastering the fundamentals to navigating the complexities, together, we’ll craft a roadmap that leads to your success in the world of Data Science and Engineering.
“Data is the new oil. It’s valuable, but if unrefined, it cannot really be used.” – Clive Humby
Unlock the potential of data and embark on a journey that transcends boundaries. Book a session with me today and let's sculpt a future brimming with endless possibilities.

Teaching Method:
I use a writing tablet and Zoom/Google Classroom for delivering lectures. My one-hour lesson plan follows the following timeline:
Revision of previous lecture/ Discussion about the last concepts.
Ice breaker activity/Introduction of the new topic.
Solving first coding exercise.
Solving next few questions with continuous input from student:.
Asking student to solve questions.
Checking student's code and giving feedback.
Closing remarks/bonding discussion/motivation.
Sending homework/ coding activity after the lecture.

Realizing Mastery Through Practice: Hands-On Learning for Lasting Understanding

In the realm of learning, experience reigns supreme. While videos from various online sources offer insights, true mastery in the domain of data science and analytics comes from active engagement and hands-on practice. I am committed not just to teaching but to ensuring that you immerse yourself in practical exercises and real-world applications.

Watching videos can offer glimpses, but it's through application and guided practice that knowledge truly takes root. My approach is centered on active participation, where concepts are not just explained but applied to tangible problems. I strive to create an environment where theoretical knowledge seamlessly merges with practical application.

In this journey, I serve as your guide, ensuring that you not only understand the theories and methodologies but also actively implement them. The emphasis is not solely on passive absorption but on active engagement, problem-solving, and the application of learned principles in real-world scenarios.

So, while external resources might provide insights, my commitment is to facilitate a learning experience that goes beyond observation. Through our sessions, you won’t just watch; you will learn by doing. Together, we'll navigate through hands-on exercises, real-life datasets, and practical projects, ensuring that every concept translates into practical proficiency.

Lastly, the Data Science life cycle involves several stages where various tools and technologies are employed. Here's an overview and we will cover most of them according to your requirement:

1. Data Collection:
Tools: Web Scrapers (Beautiful Soup, Scrapy), APIs (Requests, Selenium), Database querying (SQL), Cloud Platforms (AWS S3, Google Cloud Storage)

2. Data Preparation/Cleaning:
Tools: Pandas, NumPy, OpenRefine, Trifacta Wrangler, Databricks, Trifacta

3. Exploratory Data Analysis (EDA):
Tools: Pandas, Matplotlib, Seaborn, Plotly, Tableau, Power BI

4. Feature Engineering:
Tools: Pandas, Scikit-learn, Featuretools

5. Model Building:
Tools: Scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM

6. Model Evaluation and Validation:
Tools: Scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM

7. Model Deployment:
Tools: Flask, FastAPI, Docker, Kubernetes, AWS Lambda, Azure Functions

8. Model Monitoring and Maintenance:
Tools: Prometheus, Grafana, ELK Stack, MLflow, TensorBoard

9. Reporting and Visualization:
Tools: Power BI, Tableau, Matplotlib, Seaborn, Plotly, Dash

10. Version Control and Collaboration:
Tools: Git, GitHub, GitLab, Bitbucket

11. Big Data Processing:
Tools: Hadoop, Spark, Kafka, Hive, Pig, Flink

12. Cloud Platforms and Services:
Tools: AWS (S3, EC2, Redshift), Google Cloud Platform (BigQuery, Compute Engine), Microsoft Azure (Azure ML, Azure Databricks)

Subjects

  • Python 3 Beginner-Expert

  • Azure Data Engineer - Data Factory Beginner-Expert

  • Data engineering Beginner-Expert

  • Data Analysis using Advanced Excel Beginner-Expert

  • Python for Data science, Machine Learning and Artificial Intelligence Beginner-Expert

Experience

  • Senior Data Scientist (Dec, 2021–Present) at Solution Architect USA (Remote)
    Orchestrated the development and maintenance of data warehouses for diverse US-based clients, optimizing operational efficiency and data accessibility across various services.
    Integrate one of the Client's e-commerce B2B platform with a Fortune-500 company.
    Developed 30+ data pipelines with diverse ETL/ELT methods using Python, Spark and Databricks, ensuring seamless data flow and integrity.
    Contributed to the enhancement of operational efficiency by generating insightful Microsoft Excel reports, providing comprehensive data analysis and actionable recommendations.
    Designed and developed 40+ visually engaging reports and dashboards using Power BI and Excel, providing stakeholders with insightful data, crucial for strategic decision-making.
    Leveraged advanced SQL techniques to construct complex queries, facilitating comprehensive data retrieval and analysis for informed decision-making and cost-saving strategies.
    Collaborated cross-functionally to identify and address data-related challenges, implementing innovative solutions that improved overall data quality and accessibility.
    Played an instrumental role in the continuous improvement of data processes, ensuring compliance with industry best practices and standards.
    Actively engaged in knowledge-sharing and training, imparting expertise in Excel and SQL to enhance team capabilities.
  • Software Engineer (Feb, 2018–Dec, 2021) at Huawei Technologies Co., Ltd.
    • Developed 25+ Robotic Process Automations (RPAs), tools, and software solutions using Python, Pandas, and Selenium. Maintained 15+ RPAs, optimizing business processes for email management, Excel report generation, and data analysis, resulting in significant time and cost savings.
    • Managed SASS Servers, overseeing 10+ diverse data pipelines to ensure high availability and efficiency for scheduled reporting, including Excel automation tasks.
    • Designed Dashboards and OLAP Tabular Models, notably reducing manual reporting hours for a user base of 1500+ employees. Enhanced core business performance visualization and efficiency.
    • Implemented Big Data ETL processes with PySpark and Hadoop, facilitating the transition of customer data into Huawei SmartCare Solution for improved data management.
    • Collaborated on predictive analysis projects with Saudi telecom clients, improving ML prediction accuracy for user churn analysis and providing actionable insights for marketing campaigns, utilizing Python, SQL, Hive, and data analytics.
    • Created and implemented 60+ data analysis, AI, RPA, and BI products, significantly enhancing operational efficiency, reducing turnover, and developing dashboards and monitoring tools. Leveraged SQL queries, Excel automation and web scraping to augment project delivery cycles.
    • Provided intensive training in Python, Pandas, RPA, and Excel automation to 40 interns, while also conducting business intelligence training for 20 interns. Guided interns comprehensively through the project lifecycle, spanning from technical proficiency to delivery management, timeline supervision, and requirement gathering techniques.
    • Commenced as an intern, then swiftly advanced to lead the Automation team within 1 year. Transitioned to the role of Database Administrator (DBA) after 6 months, subsequently concluding in the position of Data Engineering team lead for the remaining duration.
    • Recognized six times as 'Employee of the Month' for consistent dedication, outstanding performance, and valuable contributions.

Education

  • Masters in Data Science (Nov, 2023–now) from University of East London. London city
  • Oracle Cloud Infrastructure Certified Data Science Professional (Jun, 2023–Sep, 2023) from Oracle–scored 96%
  • Oracle Cloud Database Migration and Integration Certified Professional (Mar, 2023–May, 2023) from Oracle–scored 95%
  • Oracle Machine Learning using Autonomous Database Certified Associate (Jan, 2023–Feb, 2023) from Oracle–scored 98%
  • Huawei Ant Robot RPA Developer, Huawei Technologies (Oct, 2022–Nov, 2022) from Huawei Technologies Co., Ltd.–scored 100%
  • Python3 Programming Specialization (Mar, 2021–May, 2021) from University of Michigan–scored 100%
  • BS Computer Sciences (Jan, 2014–Jan, 2018) from Virtual University of Pakistan Lahore–scored 3.80/ 4.0

Fee details

    Rs4,000–10,000/hour (US$14.35–35.88/hour)

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