Time is the most critical factor that decides whether a business will rise or fall. That’s why we see sales in stores and e-commerce platforms pick up pace with certain events (or festivals!). These businesses analyze years of spending data to understand the best time to throw open the gates and see an increase in consumer spending.
But how can you, as a data science professional, perform this analysis? Don’t worry, you don’t need to build a time machine! Time Series analysis is a powerful concept that acts as a gateway to understanding and forecasting trends and patterns.
Mastering time series techniques is a critical and a very in-demand skill in the industry. Come join us and learn the various components of time series analysis, how to work with time series data and build different time series models in Python!
Key Takeaways from the Workshop
- A clear and concise understanding of when to apply Time Series models and how much to rely on Time Series Analysis
- How to perform time series analysis with Python to facilitate forecasting, hypothesis testing and catastrophic event prediction
- A good understanding of Stationarity in Time Series and its importance in forecasting
- The Wold's Theorem giving rise to many popular Time Series modelling techniques
- Time series in Python with regression, Holt-Winter's approach, Box Jenkins models, the parsimonious AR-MA and the automatic selection with the popular ARIMA model
- Discussions on which scenarios fit for which kind of models. Various examples in Python to clarify understanding
- Discussions on next generation time series models and further study guidance
You will be awarded with a certificate of participation upon completion of this 2-day workshop.
- Date: 16th March - 17th March 2019
- Location: Gurgaon
- Classroom Workshop: 2 Day Workshop
- Type: Instructor Led
- Certificate: On Completion
Avinash is a Senior Data Scientist with Analytics Vidhya. He has a Data Science acumen with experience in handling complex Data Science projects and training and mentoring Data Science teams in India and abroad. He is a specialist in Natural Language Understanding and Spectral methods for data analysis. He started his journey in Data Science four years ago, prior to which he has worked as a java developer. He has a bachelors in Computer Science and a masters in IT & Operations.
Kunal is the Founder of Analytics Vidhya. Analytics Vidhya is one of largest Data Science community across the globe. Kunal is a data science evangelist and has a passion for teaching practical machine learning and data science. Before starting Analytics Vidhya, Kunal had worked in Analytics and Data Science for more than 12 years across various geographies and companies like Capital One and Aviva Life Insurance. He has worked with several clients and helped them build their data science capabilities from scratch.
Sunil Ray is Chief Content Officer of Analytics Vidhya. He brings years of experience of using data to solve business problems for several Insurance companies. Sunil has a knack of taking complex topics and then breaking them into easy and simple to understand concepts - a unique skill which comes in handy in his role at Analytics Vidhya. Sunil also follows latest developments in AI & ML closely and is always up for having a discussion on impact of technology on years to come.