Workshop Registration End Date :2024-12-23

Mentor Based

Advanced Data Science Techniques for Academicians

Data Science Mastery: Advanced Techniques for Academicians and Researchers

MODE
Virtual (Google Meet)
TYPE
Mentor Based
LEVEL
Moderate
DURATION
4 Days
START DATE
23 -December -2024
TIME
5:30 PM IST

About

The Advanced Data Science Techniques for Academicians Program provides a deep dive into data science methodologies tailored for academic use cases. Participants will learn to analyze complex datasets, build predictive models, and create impactful visualizations to enhance research output and pedagogy. The workshop combines theoretical knowledge with practical applications, enabling academicians to integrate data science into their academic and research endeavors.

Aim

This workshop is designed for academicians and researchers to gain advanced skills in data science techniques, emphasizing their applications in academic research, teaching, and innovation. The workshop focuses on equipping participants with expertise in data analysis, machine learning, and visualization using modern tools and frameworks.

Workshop Objectives

  • Equip participants with advanced data science skills for academic research.
  • Teach effective data wrangling, preprocessing, and analysis techniques.
  • Provide expertise in machine learning, NLP, and visualization tools.
  • Foster ethical data practices in academic and research environments.
  • Enable participants to complete a capstone project showcasing data science applications in their domain.

Workshop Structure

  1. Introduction to Data Science and Research
    • Overview of Data Science in academic research
    • Key challenges in handling research data
  2. Data Wrangling and Preprocessing Techniques
    • Handling missing data, outliers, and data normalization
  3. Exploratory Data Analysis (EDA)
    • Data visualization techniques for research
    • Tools for effective EDA (Python, R, and Excel)
  4. Advanced Statistical Methods for Research
    • Hypothesis testing, regression models, and ANOVA
    • Applying advanced statistical models for research insights
  5. Big Data Handling and Management
    • Introduction to big data concepts (Hadoop, Spark)
    • Working with large datasets in academic research

Day wise Schedule:

  • Day 1: Introduction to Data Science and Data Preprocessing
    • Overview of data science for academic research
    • Practical session: Cleaning and preprocessing academic datasets
  • Day 2: Exploratory Data Analysis and Visualization
    • Hands-on EDA using Python (matplotlib, seaborn) and R (ggplot2)
  • Day 3: Advanced Statistical Techniques for Research
    • Applying linear regression, ANOVA, and hypothesis testing on academic datasets
  • Day 4: Big Data and Research Management Tools
    • Introduction to big data handling tools for large-scale academic research

Intended For

Academicians, researchers, PhD scholars, and faculty members across disciplines interested in applying data science techniques to academic research.

Important Dates

Registration Ends

2024-12-23
Indian Standard Timing 1:00 pm

Workshop Dates

2024-12-23 to 2024-12-26
Indian Standard Timing 5:30 PM

Workshop Outcomes

  • Mastery of advanced data science tools and techniques tailored for academic research.
  • Ability to analyze and visualize complex datasets for impactful research outcomes.
  • Expertise in ethical data practices and the use of cloud-based data platforms.
  • Completion of a research-ready project integrating data science methodologies.

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of Currencies

FOR QUERIES, FEEDBACK OR ASSISTANCE

Key Takeaways

  • Access to Live Lectures
  • Access to Recorded Sessions
  • e-Certificate
  • Query Solving Post Workshop
wsCertificate

Future Career Prospects

  • Academic Data Scientist
  • Research Data Analyst
  • Data Science Educator
  • Higher Education Consultant
  • Researcher in Applied Machine Learning
  • Developer of Academic Data Platforms

Job Opportunities

  • Research roles in universities, think tanks, and educational institutions.
  • Consultancy positions in academic and educational technology firms.
  • Opportunities in data-driven research across various disciplines.

Enter the Hall of Fame!

Take your research to the next level!

Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.

Centre of Excellence
Join the esteemed Centre of Excellence.

Networking and Learning
Network with industry leaders, access ongoing learning opportunities.

Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).

Achieve excellence and solidify your reputation among the elite!


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Sanjeev Kumar G : 2025-04-28 at 11:35 pm

I felt
1)He should know how to operate basic teams operation because it is where he is teaching. On More Day1 he wasted 10 mins to open slide show. On Day2 he didn’t switch on the slide show though he learned it on day1 and also the slides got struck at slide 2 and he explained till slide 32(for about 30 minutes)while displaying only slide2! how can someone understand what he taught if he displays something else.
2)He is repeating the same every time. Since you are charging for what you teach! I expected I would learn something from it not just the very basics!
3)On Day1 while explaining the math he can clearly show how math calculations done rather than just showing the slides! because the RF based on calculations, he can explain it clearly.
3)I have expected he will teach what he did in the coding. But he didn’t explain the code clearly and just showed the output.
4) While giving examples in the day3, rather than just teaching the examples, he can teach how to implement because real world implementation is important.

Devisri Bandaru : 2025-04-28 at 8:37 pm

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Romario Nguyen : 2025-04-28 at 7:13 am

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