I’m Arpit Gupta, a data analytics professional with over 8 years of experience in various industries like fintech, pharmaceuticals, and internet services. I’ve had the privilege of working with companies like Moody's Analytics, Paytm, and Infoedge, where I've led teams to turn complex data into strategic business decisions. I’m passionate about helping students like you navigate the world of data analytics. Whether you’re just starting out or looking to deepen your skills, I can provide guidance on everything from mastering technical tools to understanding industry trends. My goal is to help you build a strong foundation in data analytics and develop the critical thinking skills needed to solve real-world problems. Together, we can work on projects, case studies, and career advice to ensure you’re well-prepared to succeed in this exciting field. If you’re eager to learn and ready to take the next step in your analytics journey, I’d love to mentor you.

My Mentoring Topics

• Foundations of Data Analytics: Understanding key concepts, methodologies, and tools in data analytics.
• Data Collection and Cleaning: Best practices for gathering, cleaning, and preparing data for analysis.
• Exploratory Data Analysis (EDA): Techniques for uncovering patterns, trends, and insights in data.
• Statistical Analysis: Applying statistical methods to analyze data and make informed decisions.
• Data Visualization: Creating impactful visualizations to effectively communicate data insights.
• Predictive Analytics: Building models to forecast future trends using historical data.
• Machine Learning Basics: Introduction to machine learning algorithms and their applications in analytics.
• Big Data Technologies: Overview of big data tools and frameworks like Hadoop, Spark, and NoSQL databases.
• SQL for Data Analysis: Using SQL to query and manipulate data in databases.
• Python/R for Data Analytics: Leveraging programming languages like Python or R for data manipulation and analysis.
• A/B Testing and Experimentation: Designing and analyzing experiments to validate hypotheses.
• Business Intelligence (BI) Tools: Learning BI tools like Tableau, Power BI, or Looker for data reporting and visualization.
• Data-Driven Decision Making: Using data analytics to support strategic business decisions.
• Ethics in Data Analytics: Understanding ethical considerations and biases in data analysis and AI.
• Career Pathways in Data Analytics: Exploring various roles, industries, and growth opportunities in the analytics field.