Certified Prompt Engineer For Data Science & Analytics

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Certified Prompt Engineer For Data Science & Analytics

Published 2/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 52m | Size: 4.64 GB
Unlock the Potential of Language Models in Data Science & Analytics
What you'll learn​

Understand foundational theories of natural language processing.
Explore applications of AI in data science.
Learn principles guiding effective prompt creation.
Analyze impact of language and structure on model performance.
Study advanced concepts in prompt engineering.
Anticipate complexities in designing optimized prompts.
Develop critical thinking for prompt construction.
Evaluate approaches to prompt design in data contexts.
Investigate ethical considerations in prompt engineering.
Ensure fairness and transparency in prompt usage.
Navigate data analytics with ethical integrity.
Lead data-driven decision-making initiatives.
Enhance data strategy development skills.
Position at the forefront of data science innovation.
Pursue career advancement in analytics.
Transform understanding of data science through prompt engineering.
Requirements
No prior knowledge of prompt engineering is required-just an interest in how AI and language models can enhance data analysis.
A basic understanding of data science or analytics concepts will be helpful, but the course is designed to introduce foundational theories before advancing.
Participants should have an analytical mindset and be comfortable working with structured data, as the course explores how prompts can optimize AI-driven insights.
A willingness to engage with theoretical discussions on AI, ethics, and language models will help students fully grasp the course material.
Enthusiasm for exploring new techniques in data-driven decision-making will be beneficial for applying prompt engineering to real-world analytics challenges.
Description
In the dynamic world of data science and analytics, the ability to harness the power of language models and design effective prompts is increasingly crucial. This course offers an intensive exploration into the theoretical frameworks and methodologies that underpin prompt engineering, tailored specifically for data science and analytics professionals. By delving into the intricacies of prompt construction, students will gain a robust understanding of how to leverage these tools to drive insights and innovation within their organizations.Participants in this course will embark on a journey through the foundational theories of natural language processing and artificial intelligence, focusing on their applications within data science. The curriculum is meticulously crafted to provide students with a deep understanding of the principles that guide the creation of effective prompts. Emphasizing the importance of precision and clarity, students will explore how nuanced language and structure can significantly influence the performance of language models, ultimately enhancing data analysis and interpretation.Throughout the course, students will engage with advanced concepts and theories that address the challenges and opportunities presented by prompt engineering. By examining case studies and theoretical models, students will learn to anticipate the complexities involved in designing prompts that optimize model outcomes. The course encourages critical thinking and analytical skills, enabling students to evaluate and refine their approaches to prompt construction within diverse data-driven contexts.The course also delves into the ethical considerations and implications of prompt engineering in data science. Students will explore the responsibilities of prompt engineers in ensuring fairness, transparency, and accountability in their work. By understanding the ethical dimensions of their practice, students will be better equipped to navigate the evolving landscape of data analytics with integrity and foresight.As students progress through the course, they will develop the confidence and expertise necessary to contribute meaningfully to their fields. The theoretical insights gained will empower them to lead initiatives that enhance data-driven decision-making and strategy development within their organizations. By mastering the art of prompt engineering, students will position themselves at the forefront of innovation in data science and analytics, opening new avenues for career advancement and professional growth.This course offers a unique opportunity to deepen your theoretical understanding of prompt engineering, equipping you with the knowledge and skills required to excel in the competitive field of data science and analytics. Engage with cutting-edge theories, challenge conventional thinking, and emerge as a certified expert ready to make a significant impact in your professional sphere. Join us and transform your understanding of data science through the lens of prompt engineering, and prepare to shape the future of analytics with your enhanced capabilities.
Who this course is for
Data scientists aiming to enhance their skills in prompt engineering
Analytics professionals seeking to leverage language models for insights
Individuals interested in the ethical aspects of data science
Professionals looking to innovate within data-driven organizations
Analysts eager to improve data interpretation through effective prompts
Those aspiring to lead data science initiatives with advanced skills
Learners wanting to understand AI applications in data analytics
Experts aiming to refine their approach to prompt construction
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4.64 GB | 8min 49s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

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1 -Section Introduction.mp4 (23.74 MB)
2 -Developing a Testing Framework.mp4 (73.6 MB)
3 -Techniques for Prompt Validation.mp4 (70.12 MB)
4 -AB Testing of Prompts.mp4 (83.33 MB)
5 -Analyzing Prompt Performance Metrics.mp4 (80.2 MB)
6 -Iterative Improvement of Prompt Designs.mp4 (70.11 MB)
7 -Section Summary.mp4 (21.47 MB)
1 -Section Introduction.mp4 (27.08 MB)
2 -Prompt Engineering in Business Intelligence.mp4 (88.62 MB)
3 -Enhancing Customer Experience with Prompts.mp4 (76.91 MB)
4 -Applications in Healthcare Data Analysis.mp4 (82.91 MB)
5 -Prompts for Social Media and Marketing Analytics.mp4 (84.14 MB)
6 -Future Directions in Prompt Engineering Applications.mp4 (81.82 MB)
7 -Section Summary.mp4 (23.3 MB)
1 -Conclusion.mp4 (39.86 MB)
1 -Section Introduction.mp4 (22.23 MB)
2 -Understanding Prompt Engineering.mp4 (96.59 MB)
3 -The Role of Prompts in Data Science.mp4 (90.85 MB)
4 -Importance of Context in Prompt Engineering.mp4 (88.92 MB)
5 -Key Elements of Effective Prompts.mp4 (90.39 MB)
6 -Overview of Prompt Engineering Tools.mp4 (79.88 MB)
7 -Section Summary.mp4 (20.88 MB)
1 -Section Introduction.mp4 (19.51 MB)
2 -Introduction to Data Science Concepts.mp4 (97.12 MB)
3 -Basics of Data Analytics.mp4 (90.35 MB)
4 -The Data Science Workflow.mp4 (83.84 MB)
5 -Understanding Data Types and Sources.mp4 (79.68 MB)
6 -The Role of AI and Machine Learning in Data Science.mp4 (93.77 MB)
7 -Section Summary.mp4 (21.24 MB)
1 -Section Introduction.mp4 (22.47 MB)
2 -Introduction to Natural Language Processing (NLP).mp4 (94.85 MB)
3 -NLP Techniques for Effective Prompts.mp4 (86.5 MB)
4 -Tokenization and Text Preprocessing.mp4 (82.04 MB)
5 -Sentiment Analysis and its Applications.mp4 (82.33 MB)
6 -Language Models and Their Impact on Prompts.mp4 (83.63 MB)
7 -Section Summary.mp4 (25.25 MB)
1 -Section Introduction.mp4 (23.04 MB)
2 -Crafting Clear and Concise Prompts.mp4 (79.12 MB)
3 -Aligning Prompts with Data Objectives.mp4 (85.66 MB)
4 -Techniques for Prompt Optimization.mp4 (83.65 MB)
5 -Handling Ambiguity in Prompts.mp4 (80.26 MB)
6 -Evaluating Prompt Effectiveness.mp4 (81.23 MB)
7 -Section Summary.mp4 (18.88 MB)
1 -Section Introduction.mp4 (22.51 MB)
2 -Incorporating Prompts in Data Collection.mp4 (80.7 MB)
3 -Using Prompts for Data Cleaning and Transformation.mp4 (87.39 MB)
4 -Prompts for Data Visualization and Reporting.mp4 (87.79 MB)
5 -Enhancing Predictive Models with Prompts.mp4 (90.56 MB)
6 -Automating Data Processes with Prompt Engineering.mp4 (84.99 MB)
7 -Section Summary.mp4 (24.36 MB)
1 -Section Introduction.mp4 (21.52 MB)
2 -Understanding Bias in Prompts.mp4 (105.11 MB)
3 -Ensuring Fairness and Transparency.mp4 (79.82 MB)
4 -Privacy and Security Concerns.mp4 (87.82 MB)
5 -Mitigating Misuse of Prompt Engineering.mp4 (70.14 MB)
6 -Developing Ethical Guidelines for Prompt Use.mp4 (89.15 MB)
7 -Section Summary.mp4 (24.21 MB)
1 -Section Introduction.mp4 (21.61 MB)
2 -Overview of Popular Prompt Engineering Tools.mp4 (83.77 MB)
3 -Using OpenAI GPT for Prompt Engineering.mp4 (80.29 MB)
4 -Exploring Google BERT and Other Models.mp4 (91.93 MB)
5 -Customizing Tools for Specific Needs.mp4 (87.66 MB)
6 -Evaluating Tool Performance and Suitability.mp4 (93.68 MB)
7 -Section Summary.mp4 (27.1 MB)
1 -Section Introduction.mp4 (22.78 MB)
2 -Adaptive Prompting Strategies.mp4 (71.87 MB)
3 -Dynamic Prompt Adjustments.mp4 (87.51 MB)
4 -Leveraging Multi-turn Conversations.mp4 (97.72 MB)
5 -Contextual Prompt Generation.mp4 (86.03 MB)
6 -Integrating Feedback for Continuous Improvement.mp4 (92.2 MB)
7 -Section Summary.mp4 (23.38 MB)

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