Schedules

We are in the process of finalizing the schedule, please check back this page again.

Event Schedule

Information sessions, workshops & career advice by leading education institutes in data science & AI.

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  • Day 1

    April 22, 2021

  • A lot has been said about the future of work, with terms like remote, distributed, digital and automation in heavy circulation. The future of work will require you to augment your arsenal of skills, and get very comfortable with entirely new operating models within your companies. Take a peek into the future and understand what trends are driving these shifts in the industry, and what skills can help you power ahead.
    Knowledge Sessions

  • Statistics evolved as a science in an era where the amount of data available was small and efforts were on to extract maximum actionable intelligence out of the available data. Is it still relevant in the era of Big Data,..... We will illustrate via concrete examples (from history) that while some techniques may no longer be relevant, the concepts are as relevant in this era as they were then. Indeed, ignoring them can lead to serious errors. To make the most from the available data, enormous computing power we need to combine statistical ideas with modern AIML tools to get the best results.
    Knowledge Sessions

  • The world is facing a pandemic, and a significant number of graduates and students are unsure of their future plans. Professionals have decided to switch careers completely, and others are struggling to pick an industry they will earn a living in. It is clear that no matter what career we choose, we need to upskill to gain the necessary momentum required to thrive in today's market. This talk will help us understand the relevant upskilling trends in technology, management, and data. We shall see what Industry 4.0 is expecting from the new generation of changemakers.
    Knowledge Sessions

  • Campus placements are one of the important factors that students consider before choosing a college. Being employed right after graduating is definitely a priority to them, and students could do with all the assistance they get from the college. That is why colleges that offer a higher percentage of placements are preferred over others. But there is one important fact about campus placements that students tend to overlook. This session will help you understand how the college helps you land your first job in the field of Data Science. Hear from the current members of the PlaceComm and the Head of Corporate Relations at Praxis as they help you decode why placements start as early as 4:30 AM on day zero at Praxis. The discussion will cover the following: 1. The surge in demand for data science professionals in COVID times 2. Campus placement opportunities across academic backgrounds and industry experience – from fresh college graduates to people with 10 years or more of experience 3. The diversity of companies and profiles on offer in this exciting domain 4. The kind of skills and competencies enterprises look for 5. How does one start and accomplish the journey to the first real job in the data science domain Praxis Business School is one of the earliest institutes that recognized the boom and dynamism around data analysis in business, and has graduated and placed 23 batches of data scientists from its Kolkata and Bangalore campuses.
    Knowledge Sessions

  • Possessing data science skills has become essential to enhancing an individual’s employability in today’s global economy. INSOFE’s executive programs designed in collaboration with Case Western Reserve University and Rennes School of Business make data science knowledge accessible to working professionals who do not have the luxury to attend full time classes. This talk will also discuss pathways for 4-9 year experienced engineers and managers in addition to the education opportunities available for senior leaders.
    Knowledge Sessions

  • Training vision-based Autonomous driving models is a challenging problem with enormous practical implications. One of the main challenges is the requirement of storage and processing of vast volumes of (possibly redundant) driving video data. In this talk, we discuss the problem of data-efficient training of autonomous driving systems. References: 1. Multi-criteria online Frame-subset Selection for Autonomous Vehicle Videos Soumi Das, Sayan Mandal, Ashwin Bhoyar, Madhumita Bharde, Niloy Ganguly, Suparna Bhattacharya, and Sourangshu Bhattacharya. Pattern Recognition Letters (2020) 2. Das, Soumi, Harikrishna Patibandla, Suparna Bhattacharya, Kshounis Bera, Niloy Ganguly, and Sourangshu Bhattacharya. "Convex Online Video Frame Subset Selection using Multiple Criteria for Data Efficient Autonomous Driving." arXiv preprint arXiv:2103.13021 (2021).
    Knowledge Sessions

  • There’s never been a more exciting time to get into Data Science. From hospitals providing personalised Cancer patient care to predicting when the next financial crash will happen, Data is an essential part of society that in a post-pandemic world will become increasingly important in how we go about our daily lives. In this talk, I’ll share an insight into how you can get into this exciting field. Some of the areas I’ll speak about include: • Getting started with Data Science. • Building knowledge: Best ways to learn. • Recommended tools and learning Resources • Where Data Science can take you.
    Knowledge Sessions

  • Gartner says 80% of data science pilots will not deliver any business outcome and fail to go into production till 2022. Based on my 17+ years of experience with data science and AI projects, most failures happen when companies do not know what they are looking for from the data. It is of paramount importance that we take a structured approach towards building AI products right from the beginning. Early learners while understanding the nuts and bolts of data science, should also focus on acquiring knowledge and skills that help them build successful AI products that solve pressing business problems. In this talk I will focus on the Crisp -DM framework, elaborating on each of the components that go into building production-ready AI/ML taking examples from my past experiences and challenges. I have made few extensions to the Crisp-DM framework to highlight the importance of asking the right business questions at the beginning of a data science project. Also, I will provide few tips on how to engage with the clients, business users, and stakeholders at every phase of the project for the successful adoption of AI amongst them.
    Knowledge Sessions

  • One of the most attractive career options in the present time is that of an Analytics and Data Science professional. Apart from great salary packages, a career in this field has the long-term potential of delivering a substantial positive impact on society. However, those desirous of this attractive career option need to be aware that it requires a lot of preparation and hard work. A good mastery of both techniques and domain knowledge is expected, none of which is easy to acquire. Besides, the rapid pace of progress in this field makes learn-unlearn-relearn the only viable paradigm for long-term career success.
    Knowledge Sessions

  • Know what you want but not how to start? That's the kind of question you surface very often when considering a career option. This talk will discuss the concept of artificial intelligence and its subsets in detail talks about artificial intelligence as a career option, and also takes you through its salary trends observed and predicted for an artificial intelligence oriented job role.
    Knowledge Sessions

  • In the digital age, Data is the new oil and data engineers are the experts in the company who understand the various sources and forms the data comes from, how it is to be stored, how can it be made easily accessible at a time and in the format required, how it should be protected – thus enabling the company to make use of the data for business growth. Though anyone with the right set of technical competencies and aptitude can be groomed as a Data Engineer, people with a background in Science and Engineering are the ones who are most preferred and suited for the job. The ideal candidate needs to be comfortable with the notion of working data and making sure that (s)he has the interest to handle different kinds of systems and technologies. Large companies like Amazon, Facebook or Google have massive amounts of data that needs to be managed – so that Amazon can make the right recommendations and Google can give the right search results in very quick time. This requires knowledge of a number of tools and technologies, including Cloud and Big Data systems, and also understanding of all the processes that data goes through. This is only possible due to the contribution of a large army of data engineers working smartly to manage all the data. Do you think you have it in you to be a part of the data economy that nurtures the data pipelines behind the billion-dollar industry - come and join the session where experts from Academics & Industry share their insight and roadmap for “Data Engineering - the fastest growing Tech Job” on 22nd April at Skillup 2021.
    Knowledge Sessions

  • Digitization of education has paved an amazing way for us to acquire or enhance the most relevant skills. The entire skilling landscape gives a lot of options to an individual to embark on the learning journey but it's critical to choose the right path. In this talk, we will talk about the types of online education, how to choose the best learning path, how mentored learning guides you through all difficulties, how are online degrees changing the education landscape and what the future holds for all of us.
    Knowledge Sessions

  • As the young undergraduate aspires to become data scientists, they always wonder how they can become a data scientist. In this talk, I will discuss how young data science aspirants can prepare themselves to study the subject like (1) Calculus; (2) Matrix Algebra; (3) Probability and Statistics; and (4) Programming and Data Structure. What are open-source materials are available that they should look for?
    Knowledge Sessions

  • This session will focus on the best skills to have and/or work on to excel in the current market. Will also include few tips to really focus on the impact to the business, staying far from seasonal "buzzwords" that are continuously connected to the data science world.
    Knowledge Sessions

  • If data is the new oil - the catalyst for economic growth in the 21st century - then data science must take on the initiative to help organizations extract and monetize the customer, product and operational insights buried their data. The Data Science 2.0 challenge is to move beyond the AI / ML technologies and data science competencies, and champion a methodology for exploiting the economic value of data and analytics; to transition from just providing analytic outputs to delivering material and meaningful business and operational outcomes.
    Knowledge Sessions

  • Day 2

    April 23, 2021

  • Data Science is finding its applications in almost every discipline and there is an increasing demand for domain specialists with advanced knowledge of data science skills. This talk will demonstrate the importance of dual specialization masters in data science to meet this challenge and discuss INSOFE programs designed in collaboration with global universities in the U.S.A, Canada, and Europe for individuals from diverse academic disciplines. We will further discuss the exciting career opportunities and work visa options available to all our students upon graduating from the program.
    Knowledge Sessions

  • Workshop demo: " How a raw functional data stored in a DB can be used to build an AIML enabled prediction model followed by a clickable application and decision dashboard " Session breakup:- · Understand what is AIML [ 20 mins ] · Understand how AIML is enabling businesses and enhancing their decision power [ 20 mins ] · AIML fullstack case study building [ 50 mins ] · Q&A [ 20 mins ] · Conclusion [ 5 mins ]
    Workshops

  • In this workshop, we are bringing a step by step flow to explain the path to becoming a Data Scientist and need to learn Python for the data science journey. We will learn about different landscapes in Artificial Intelligence, the basics of Python programming, understanding the importance of data analysis and visualisations. Hands-on session on regression, classification and clustering and many more. Topics: 1. Artificial Intelligence, Machine Learning & Deep Learning 2. Introduction to Python Programming 3. Hands-on linear algebra and statistics with SciPy and Numpy 4. Hands-on Data analysis, manipulation, and visualization with Pandas and Matpltlib 5. Hands-on session Machine learning with Scikit-learn 6. Applications of Machine Learning Key Takeaways: A hands-on session to Machine Learning libraries Certificate for Hands-on sessions on Data Science and Machine Learning Kickstart your Data Science journey Required Tools: Any editor to run the python programs (preferably Google Colab Notebooks) High-speed internet connection with a Laptop/ Computer
    Workshops

  • AIM Data Science Faculty Excellence Awards recognizes and celebrates excellence in data science education on a Global scale. This Award honor exceptional teaching and culminate in a grand award ceremony at SkillUp 2021. Our vision is a teaching profession with high morale and a data science ecosystem that values and celebrates the great work that is done by faculties and leaders in education.
    Knowledge Sessions

  • AI and Data Science are no longer buzz words – they are all around us. The important question today for young professionals and graduating students is “how can I excel in this changed world”. This talk goes into the key skills and capabilities required for navigating this increasingly uncertain and unstructured world.
    Knowledge Sessions

  • Co-founded by 60+ CXOs, Plaksha Tech Leaders Fellowship (TLF) is a one year full-time residential post-graduate program co-designed and co-delivered by UC Berkeley. The first-of-its-kind, TLF interweaves Artificial Intelligence (AI) and Machine Learning (ML) with real-world application, leadership and mentorship. The program has been designed to create Tech Leaders who will lead organizations, build path-breaking ventures and help solve real world challenges for India and the world. Program Highlights Faculty from UC Berkeley, UPenn, Purdue University, IIT Bombay, Google and Microsoft Experiential, innovative and technically deep curriculum Interweaves AI and ML with real world applications, leadership and mentoring Need and merit based scholarships offered
    Knowledge Sessions