Dear Readers,
Data Science is a vast subject, and the learning you can get is immense. And we at Analytics Vidhya always try to bring new learning topics and build up your skills. This time, we have not one, not two, but six new DataHour for you to attend. So, keep your notepad handy and get ready to brush up on your skills with our industry experts. 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: Think like a Data Scientist
Computational power is a significant problem that today’s data scientists must overcome. Companies are looking for experts that can efficiently derive forecasts from raw data. The data scientists must treat the raw data carefully and extract the required features for the model of their choosing if they are to make accurate predictions. The general idea is that selecting the model and giving it the necessary optimization is one method to get more favorable forecasts. In this DataHour, learn practically about the thought process every data scientist should possess to make the machine learning models more robust. Register for the data hour here!
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Learn with the industry expert Anudeep Sri B.
He is a Graduate Research Assistant at the University of Massachusetts, Dartmouth. He has 6 years of experience driving in any size and format of data towards insights and predictions using Azure cloud services, Bigdata and AI. Further, he has also delivered 21 guest lectures on AI & Cloud Computing at various international platforms and Universities. Are you ready to think like a data scientist with him?
DataHour: Introduction to Explainable AI (XAI)
Explainable AI, also known as XAI, is the use of artificial intelligence so that human beings can comprehend the consequences of the solution. Avik will introduce you to the idea of XAI in this DataHour and discuss such subjects as why machine learning, where machine learning fits in, why XAI, the necessity of AI audit, and ethical AI.
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Avik Das, a Scientist at Tata Consultancy Services (TCS), is an expert who can teach you. He has more than six years of expertise in the field of analysis. He has extensive experience in data modeling, validation, pricing analytics, sales forecasting, scheme analysis, and predictive analytics. He has practical expertise using advanced Excel, R, Python, Spark, Tableau, PowerBi, Xlminer, and Solver.
DataHour: MLOps—DevOps for Machine Learning
Join this DataHour to discover how MLOps—DevOps for machine learning—can be used to manage the whole machine learning lifecycle, including straightforward deployment from movie genre prediction. This session will teach you how to:
- Create, develop, and use machine learning models.
- To produce more quickly, manage the production workflows.
- Automate the machine learning lifecycle to update, validate, and deploy new models continuously.
DataHour: Stirring up Data Science with SQL
Nobody can enter the field of data science more effectively than through studying SQL. In addition to being one of the most in-demand abilities for data professionals, SQL also acts as a springboard for developing other important tech skills. The foundation of many lucrative data science employment is the SQL programming language.
Join Uddipta Sarma, a data science trainer, as she explores some intriguing SQL queries in this DataHour. These queries include SELECT, SELECT DISTINCT, WHERE, AND, OR, NOT, DELETE, TRUNCATE, UPDATE, MATH FUNCTIONS, STRING FUNCTIONS, GROUP BY, HAVING, ORDER BY, etc.
DataHour: Leveraging GCP Vertex AI for Machine Learning
Vertex AI is a scalable platform for AI/ML use cases on the Google Cloud Platform (GCP). Building, deploying, and scaling machine learning models more quickly is made possible by pre-trained and bespoke tooling within a single artificial intelligence platform.
DataHour: Quantum Computing Simulator Acceleration
For several categories of hitherto difficult problems, quantum computing aims to provide more potent computation and quicker outcomes. Understanding quantum processing and creating quantum algorithms depend on quantum circuit modeling. Parallel processing is used in accelerated computing to speed up work on complex applications, such as simulations and visualizations and AI and data analytics. The NVIDIA cuQuantum SDK contains optimized libraries and tools for quickening workflows related to quantum computing. A pioneering platform for hybrid quantum-classical computers, NVIDIA Quantum-Optimized Device Architecture (QODA) enables the integration and programming of quantum processing units (QPUs), GPUs, and CPUs in a single device.
Conclusion
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.Connect
If you’re having trouble enrolling or would like to conduct a session with us. Contact us at [email protected]
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