Data Analytics Workshop
The internet has revolutionized the world leading to an age of connectivity. It has pushed the boundaries of machine intelligence by enabling sophisticated computing algorithms to be developed and imparting them the ability to efficiently harness large data aggregations. The ability to understand the data and analyzing it effectively through computer algorithms is increasingly becoming an essential skill irrespective of one’s profession. Data analytics has significantly altered social dynamics and world order. It is imperative that students and young professionals understand its importance and impact on the positive influences as well as the drawbacks. Further, with advances in data science, artificial intelligence, and machine learning, algorithmic programming has become a necessity for all engineers to tackle different social issues. This workshop aims at introducing the participants into the field of advanced data analytics with python and building their expertise in the development of a variety of data management strategies and applications.
Workshop Session – I: Fundamentals of Data Handling
In Session 1 of the workshop series, the basic concepts of python for data science will be discussed. The topics include the importance of python in data analysis, python data structures (containers such as lists, sets, dictionaries and arrays), a brief overview of important libraries for data handling (such as NumPy, SciPy, Matplotlib, Pandas, Scikit-learn) and a detailed introduction to NumPy. Some practice programs will be discussed along with introducing the participants to hands-on programming on the discussed topics.
Tutors: Nandakishor Desai, Sourav Mondal
Workshop Session – II: Data Preprocessing and Visualization
Session 2 of the workshop series begins with a detailed introduction to Pandas, Matplotlib and Scipy. Matplotlib is a powerful visualization tool for initial data exploration and understanding. An important library for a diverse range of data analysis techniques is Pandas that includes well-organized data structures, file handling capabilities and efficient data preprocessing/management functions. Some practice programs will be discussed covering visualization and basics of file handling.
Tutors: Nandakishor Desai, Sourav Mondal
Workshop Session III: Data Processing and Exploration
In the third session, the essential steps of data analysis will be discussed in further details including a detailed introduction to data wrangling. Further, some explorative data analysis techniques (basic statistical approaches, descriptive statistics etc…) will be discussed. Further, some basic machine learning concepts for advanced data analysis and associated libraries such as sci-kit learn will be discussed. This session will conclude with some hands-on analysis for some simple and practical applications in real-life.
Tutors: Nandakishor Desai, Sourav Mondal
Workshop Session IV: Time Series Data Analysis
In the fourth and concluding session, we will have an interactive session to clear any doubts from the proceeding sessions. Further, we will solve some data analysis projects covering time series and other trends.
Tutors: Nandakishor Desai, Sourav Mondal