Online/ e-LMS
Mentor Based
Advanced
8 weeks
About
NumPy – Use in AI is a comprehensive 8-week course designed to introduce M.Tech, M.Sc, and MCA students, as well as E0 & E1 level professionals, to the powerful NumPy library. It covers the essential techniques required for efficient numerical computations in AI, including operations on large arrays and matrices, which are pivotal in machine learning and data analysis tasks.
Aim
This course aims to provide participants with a foundational understanding of NumPy, focusing on its critical role in data handling and numerical computation for AI applications.
Program Objectives
- Mastering NumPy: Comprehensive understanding of NumPy’s functionalities and its application in AI.
- Efficient Data Handling: Skills to handle and process large datasets efficiently using NumPy.
- AI Implementation Skills: Ability to integrate NumPy with AI models and other Python libraries for robust AI solutions.
Program Structure
- Introduction to NumPy:
- Basics of NumPy and setting up the environment.
- Understanding NumPy arrays, data types, and array manipulations.
- NumPy in Data Handling:
- Advanced techniques in indexing, slicing, reshaping, and transposing arrays.
- Statistical analysis capabilities of NumPy for AI applications.
- NumPy for Machine Learning:
- Utilization of NumPy in feature engineering for AI models.
- Techniques to improve computation efficiency through vectorization and broadcasting.
- NumPy with Other Libraries:
- Integrating NumPy with Pandas for data analysis and Matplotlib for data visualization.
- Practical applications in building neural networks and processing image and audio data.
- Real-World AI Applications Using NumPy:
- Implementation of NumPy in various AI-driven projects and how to scale these solutions.
Participant’s Eligibility
- Advanced students (M.Tech, M.Sc, MCA) and professionals in IT, data science, and related fields seeking to enhance their skills in numerical computing and AI.
Program Outcomes
- Advanced Numerical Skills: Deep knowledge and practical experience with NumPy’s powerful array functions.
- AI Application Mastery: Skills to apply NumPy in developing and tuning AI models.
- Industry Readiness: Preparedness to tackle real-world data challenges using advanced AI and numerical techniques.
Fee Structure
Standard Fee: INR 31,998 USD 858
Discounted Fee: INR 15999 USD 429
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 CurrenciesBatches
Live
Certificate
Program Assessment
Certification to this program will be based on the evaluation of following assignment (s)/ examinations:
| Exam | Weightage |
|---|---|
| Mid Term Assignments | 50 % |
| Project Report Submission (Includes Mandatory Paper Publication) | 50 % |
To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.
Program Deliverables
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Placement Assistance
- Industry Integration: Insights from AI industry leaders and data scientists who utilize NumPy.
- Job Placement Support: Assistance in securing roles that require proficiency in numerical computation and AI technologies.
- Professional Networking: Opportunities to connect with a network of AI professionals and industry experts.
Future Career Prospects
- Data Scientist: Utilizing NumPy for complex data analysis tasks.
- AI Developer: Developing and optimizing AI algorithms using NumPy.
- Research Analyst: Conducting advanced numerical simulations and analyses for AI research.
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Recent Feedbacks In Other Workshops
The course was well communicated and interactive
lecture delivered well but the title of workshop was a little misleading
