The DataHour: Your Upcoming Data Science Learnings!
Fellow Data Science Enthusiasts, The only way to move forward in your career ladder is by learning and unlearning. And the best way to do that is by adding some new skills to your CV. And Analytics Vidhya comes forward to help you with this. With the new learning topics, get ready to brush up on your skills with our lined-up DataHour sessions. Check out the list for upcoming DataHour below, and register yourself now! Prerequisites for registering: Enthusiasm to learn Data Science
For whom is this DataHour for?
- Students and Freshers with an interest in Data Science.
- Data science professionals who want to accelerate their career growth
DataHour: Anomaly detection using NLP and Predictive Modeling
Most engineering organizations use computerized job scheduling to coordinate daily operations among many departments. These domains include data engineering, client targeting, campaign management, and order management. These jobs are frequently scheduled in the hundreds of thousands, if not more, daily, making the job management and exception handling component challenging, time-consuming, and resource-intensive.
Learn with the industry expert Paritosh Sinha, Senior Data Scientist at Uber. He is a tenured data scientist with more than 10 years of experience utilizing machine learning, statistical, and NLP techniques to address business challenges in consulting, services, and product-based enterprises. He is a problem solver, a quick learner, and an experienced team leader. He is currently employed with Uber’s marketing division as a Senior Data Scientist.
DataHour: Google Cloud AI/ML
Learn from the industry expert Mona Mona, an AI/ML customer engineer at Google. She has more than 10 years of experience in software design, development, and integration across various work contexts. She is a highly experienced IT professional. Before joining Google, she was a Senior Machine Learning Solution Architect at Amazon Web Services. Her responsibility was to guarantee client success when developing products and services on the AWS platform.
DataHour: Energy Data Science – Project From Scratch
In this DataHour, you’ll get a good sneak peek into what kind of Data, Processing & Projects happen in the Oil & Energy sector. You will obtain knowledge of the raw data from an oil-producing field, such as the water injector well data and oil well data.
The primary emphasis will be on the data processing phases at the core of many Industrial Data Science workflows. We’ll discuss descriptive statistics, outlier detection, feature engineering, and null handling. The session will come to a close with an introduction to machine learning.
Learn from the industry leader Divyanshu Vyas, Founder of Petroleum From Scratch and Energy Data Scientist. His philosophy is “be the perfect balance of Physics & Mathematics.” He works as a Machine Learning & Data Science Consultant for Oil & Energy Projects and as a Community Mentor for Python and Data Sciences for the Energy Industry.
DataHour: Getting Started with EDA tools – Numpy and Pandas
Learn from Jaiyesh Chahar, a Data Scientist at Siemens and an industry specialist. Jaiyesh works for Siemens as a data scientist and serves as a community mentor for the oil and gas industry’s use of Python and data science. Petroleum from Scratch’s co-founder: A venture focused on teaching the community fundamental petroleum concepts and data analytics skills that aid both professionals and students in developing the skills required for Industry 4.0.
So, if you want to add new skills to your resume, then Register now and grab this amazing opportunity to learn with the experts. If you’re attending this session and have some questions about this topic, please send them to us at [email protected], or ask directly to the speaker during the session. If you missed any past episodes of ‘The DataHour,’ you may watch the recordings on our YouTube channel or read the synopsis here.
If you’re having trouble enrolling or would like to conduct a session with us. Contact us at [email protected]