#chatgpt prompt engineering course

[genzeeacademy]

[businessiideahindi]

Prompt Engineering से पैसे कमाएँ |Unique way to earn money online..

Prompt Engineering : online सफलता के लिए प्रभावी Prompt डिज़ाइन करना | Online संचार के तेजी से विकसित हो रहे परिदृश्य में, Prompt Engineering एक महत्वपूर्ण कौशल के रूप में उभरी है, जो जुड़ाव बढ़ाने, बहुमूल्य जानकारी देने और यहां तक ​​कि डिजिटल इंटरैक्शन का मुद्रीकरण करने का मार्ग प्रशस्त कर रही है। यह लेख Prompt Engineering की दुनिया पर गहराई से प्रकाश डालता है, इसके महत्व, सीखने के सुलभ…

[jcmarchi]

MIT faculty, instructors, students experiment with generative AI in teaching and learning

New Post has been published on https://thedigitalinsider.com/mit-faculty-instructors-students-experiment-with-generative-ai-in-teaching-and-learning/

MIT faculty, instructors, students experiment with generative AI in teaching and learning

How can MIT’s community leverage generative AI to support learning and work on campus and beyond?

At MIT’s Festival of Learning 2024, faculty and instructors, students, staff, and alumni exchanged perspectives about the digital tools and innovations they’re experimenting with in the classroom. Panelists agreed that generative AI should be used to scaffold — not replace — learning experiences.

This annual event, co-sponsored by MIT Open Learning and the Office of the Vice Chancellor, celebrates teaching and learning innovations. When introducing new teaching and learning technologies, panelists stressed the importance of iteration and teaching students how to develop critical thinking skills while leveraging technologies like generative AI.

“The Festival of Learning brings the MIT community together to explore and celebrate what we do every day in the classroom,” said Christopher Capozzola, senior associate dean for open learning. “This year’s deep dive into generative AI was reflective and practical — yet another remarkable instance of ‘mind and hand’ here at the Institute.”  

Play video

2024 Festival of Learning: Highlights

Incorporating generative AI into learning experiences 

MIT faculty and instructors aren’t just willing to experiment with generative AI — some believe it’s a necessary tool to prepare students to be competitive in the workforce. “In a future state, we will know how to teach skills with generative AI, but we need to be making iterative steps to get there instead of waiting around,” said Melissa Webster, lecturer in managerial communication at MIT Sloan School of Management. 

Some educators are revisiting their courses’ learning goals and redesigning assignments so students can achieve the desired outcomes in a world with AI. Webster, for example, previously paired written and oral assignments so students would develop ways of thinking. But, she saw an opportunity for teaching experimentation with generative AI. If students are using tools such as ChatGPT to help produce writing, Webster asked, “how do we still get the thinking part in there?”

One of the new assignments Webster developed asked students to generate cover letters through ChatGPT and critique the results from the perspective of future hiring managers. Beyond learning how to refine generative AI prompts to produce better outputs, Webster shared that “students are thinking more about their thinking.” Reviewing their ChatGPT-generated cover letter helped students determine what to say and how to say it, supporting their development of higher-level strategic skills like persuasion and understanding audiences.

Takako Aikawa, senior lecturer at the MIT Global Studies and Languages Section, redesigned a vocabulary exercise to ensure students developed a deeper understanding of the Japanese language, rather than just right or wrong answers. Students compared short sentences written by themselves and by ChatGPT and developed broader vocabulary and grammar patterns beyond the textbook. “This type of activity enhances not only their linguistic skills but stimulates their metacognitive or analytical thinking,” said Aikawa. “They have to think in Japanese for these exercises.”

While these panelists and other Institute faculty and instructors are redesigning their assignments, many MIT undergraduate and graduate students across different academic departments are leveraging generative AI for efficiency: creating presentations, summarizing notes, and quickly retrieving specific ideas from long documents. But this technology can also creatively personalize learning experiences. Its ability to communicate information in different ways allows students with different backgrounds and abilities to adapt course material in a way that’s specific to their particular context. 

Generative AI, for example, can help with student-centered learning at the K-12 level. Joe Diaz, program manager and STEAM educator for MIT pK-12 at Open Learning, encouraged educators to foster learning experiences where the student can take ownership. “Take something that kids care about and they’re passionate about, and they can discern where [generative AI] might not be correct or trustworthy,” said Diaz.

Panelists encouraged educators to think about generative AI in ways that move beyond a course policy statement. When incorporating generative AI into assignments, the key is to be clear about learning goals and open to sharing examples of how generative AI could be used in ways that align with those goals. 

The importance of critical thinking

Although generative AI can have positive impacts on educational experiences, users need to understand why large language models might produce incorrect or biased results. Faculty, instructors, and student panelists emphasized that it’s critical to contextualize how generative AI works. “[Instructors] try to explain what goes on in the back end and that really does help my understanding when reading the answers that I’m getting from ChatGPT or Copilot,” said Joyce Yuan, a senior in computer science. 

Jesse Thaler, professor of physics and director of the National Science Foundation Institute for Artificial Intelligence and Fundamental Interactions, warned about trusting a probabilistic tool to give definitive answers without uncertainty bands. “The interface and the output needs to be of a form that there are these pieces that you can verify or things that you can cross-check,” Thaler said.

When introducing tools like calculators or generative AI, the faculty and instructors on the panel said it’s essential for students to develop critical thinking skills in those particular academic and professional contexts. Computer science courses, for example, could permit students to use ChatGPT for help with their homework if the problem sets are broad enough that generative AI tools wouldn’t capture the full answer. However, introductory students who haven’t developed the understanding of programming concepts need to be able to discern whether the information ChatGPT generated was accurate or not.

Ana Bell, senior lecturer of the Department of Electrical Engineering and Computer Science and MITx digital learning scientist, dedicated one class toward the end of the semester of Course 6.100L (Introduction to Computer Science and Programming Using Python) to teach students how to use ChatGPT for programming questions. She wanted students to understand why setting up generative AI tools with the context for programming problems, inputting as many details as possible, will help achieve the best possible results. “Even after it gives you a response back, you have to be critical about that response,” said Bell. By waiting to introduce ChatGPT until this stage, students were able to look at generative AI’s answers critically because they had spent the semester developing the skills to be able to identify whether problem sets were incorrect or might not work for every case. 

A scaffold for learning experiences

The bottom line from the panelists during the Festival of Learning was that generative AI should provide scaffolding for engaging learning experiences where students can still achieve desired learning goals. The MIT undergraduate and graduate student panelists found it invaluable when educators set expectations for the course about when and how it’s appropriate to use AI tools. Informing students of the learning goals allows them to understand whether generative AI will help or hinder their learning. Student panelists asked for trust that they would use generative AI as a starting point, or treat it like a brainstorming session with a friend for a group project. Faculty and instructor panelists said they will continue iterating their lesson plans to best support student learning and critical thinking. 

Panelists from both sides of the classroom discussed the importance of generative AI users being responsible for the content they produce and avoiding automation bias — trusting the technology’s response implicitly without thinking critically about why it produced that answer and whether it’s accurate. But since generative AI is built by people making design decisions, Thaler told students, “You have power to change the behavior of those tools.”

[harisystems]

What is Prompt Engineer - Prompt Engineer Courses by Open AI - AI - Chat...

[theeuniversesays]

Expert_Juwelier

2 days agoPrompt Engineering is the Alchemy of the Digital Age: turning words into actions, dreams into software. ?

✨ If coding was the job of yesterday, crafting the perfect prompt is tomorrow

#TechTrends #AIRevolution#TechInsights#promptengineering#chatgpt4

[blackjackkent]

Here is the thing that bothers me, as someone who works in tech, about the whole ChatGPT explosion.

The thing that bothers me is that ChatGPT, from a purely abstract point of view, is really fucking cool.

Some of the things it can produce are fucking wild to me; it blows my mind that a piece of technology is able to produce such detailed, varied responses that on the whole fit the prompts they are given. It blows my mind that it has come so far so fast. It is, on an abstract level, SO FUCKING COOL that a computer can make the advanced leaps of logic (because that's all it is, very complex programmed logic, not intelligence in any human sense) required to produce output "in the style of Jane Austen" or "about the care and feeding of prawns" or "in the form of a limerick" or whatever the hell else people dream up for it to do. And fast, too! It's incredible on a technical level, and if it existed in a vacuum I would be so excited to watch it unfold and tinker with it all damn day.

The problem, as it so often is, is that cool stuff does not exist in a vacuum. In this case, it is a computer that (despite the moniker of "artificial intelligence") has no emotional awareness or ethical reasoning capabilities, being used by the whole great tide of humanity, a force that is notoriously complex, notoriously flawed, and more so in bulk.

-----

During my first experiment with a proper ChatGPT interface, I asked it (because I am currently obsessed with GW2) if it could explain HAM tanking to me in an instructional manner. It wrote me a long explanatory chunk of text, explaining that HAM stood for "Heavy Armor Masteries" and telling me how I should go about training and preparing a character with them. It was a very authoritative sounding discussion, with lots of bullet points and even an occasional wiki link Iirc.

The problem of course ("of course", although the GW2 folks who follow me have already spotted it) is that the whole explanation was nonsense. HAM in GW2 player parlance stands for "Heal Alacrity Mechanist". As near as I've been able to discover, "Heavy Armor Masteries" aren't even a thing, in GW2 or anywhere else - although both "Heavy Armor" and "Masteries" are independent concepts in the game.

Fundamentally, I thought, this is VERY bad. People have started relying on ChatGPT for answers to their questions. People are susceptible to authoritative-sounding answers like this. People under the right circumstances would have no reason not to take this as truth when it is not.

But at the same time... how wild, how cool, is it that, given the prompt "HAM tanking" and having no idea what it was except that it involves GW2, the parser was able to formulate a plausible-sounding acronym expansion out of whole cloth? That's extraordinary! If you don't think that's the tightest shit, get out of my face.

----

The problem, I think, is ultimately twofold: capitalism and phrasing.

The phrasing part is simple. Why do we call this "artificial intelligence"? It's a misnomer - there is no intelligence behind the results from ChatGPT. It is ultimately a VERY advanced and complicated search engine, using a vast quantity of source data to calculate an output from an input. Referring to that as "intelligence" gives it credit for an agency, an ability to judge whether its output is appropriate, that it simply does not possess. And given how quickly people are coming to rely on it as a source of truth, that's... irresponsible at best.

The capitalism part...

You hear further stories of the abuses of ChatGPT every day. People, human people with creative minds and things to say and contribute, being squeezed out of roles in favor of a ChatGPT implementation that can sufficiently ("sufficiently" by corporate standards) imitate soul without possessing it. This is not acceptible; the promise of technology is to facilitate the capabilities and happiness of humanity, not to replace it. Companies see the ability to expand their profit margins at the expense of the quality of their output and the humanity of it. They absorb and regurgitate in lesser form the existing work of creators who often didn't consent to contribute to such a system anyway.

Consequently, the more I hear about AI lately, the more hopeful I am that the thing does go bankrupt and collapse, that the ruling goes through where they have to obliterate their data stores and start over from scratch. I think "AI" as a concept needs to be taken away from us until we are responsible enough to use it.

But goddamn. I would love to live in a world where we could just marvel at it, at the things it is able to do *well* and the elegant beauty even of its mistakes.

[bright-and-burning]

okay yeah i didn't know that there's the different ai stuff and that this is generative ai BUT GOD AM I HAPPY to see that you know the difference between ai and ml like !!! this is not ai !!! it's such a trend now and it's so wrong and so frustrating beyond the, in this case, misogynistic aspects of it. like this is not ai !! but that sounds catchy and URGH so frustrating. okay that's all i love ur additional tags thank u xoxo

yeah!! i did my undergrad degree focused on this kind of stuff (and dropped out of doing a phd in it at the last minute) so it's Literally my roman empire. like. i took so many courses in this and THEN it blew up right at the end of my degree and the misinformation........ chatgpt getting massive my senior year of college made me soooo mad i legit started to resent my field. like this particular use is particularly egregious (why hire a woman in an area severely lacking in women when we can rampantly misuse important computational and REAL LIFE resources to create a fake woman to "talk" abt SUSTAINABILITY!!!) but in general i am like constantly infuriated by AI bullshit from a lot of different sides bc Everyone overestimates/glorifies it/turns it into something it isn't, essentially. (rant abt AI from an AI perspective under the cut that idk might be informative or interesting LOL. i tried not to get technical but i did get mad)

generative ai drives me BONKERS bc it's literally not artificial intelligence. chatgpt is NOT AI it's fucking glorified predictive chat and all the dumbass tech bros on linkedin and twitter who hail it as like world changing infuriate me lol. like chatgpt literally works by calculating the word with the highest probability to come next in the sentence/in response to that prompt based on the data it trained on. is that super impressive ignoring the real world stuff going on? yeah!! it is! it's doing really well and it's fascinating in an academic sense. but then you put it in the real world context, where dumbass tech bros and business leaders worship it as god and where SEO morons use it to turn the internet to sludge and it's like oh god WHY.

and the ai art bullshit oh my god. ok i took a machine vision class right. and like literally one of my projects was to write code that could take in a photo and output it in the "style" of another photo. like as the cs version of a creative exercise, basically (they give u a Lot of projects that are basically write ur own version of an algorithm that's already been written more efficiently by someone else, bc that's how you can kind of pick it apart and really understand it, it's like reverse engineering) to show us how that works. (photos from that project are below; i took the cactus photo and then i "combined" it with a monet. i am STAUNCHLY anti-ai "art" btw this was Lich rally an assignment lol). but do you know what i learned (and what my whole class learned)? it's not fucking magic. it's LINEAR ALGEBRA. it's linear algebra on a truly batshit crazy level, combined with some crazy optical physics equations, but it's literally math. technically speaking, if you had infinite time, and were really insanely good at math (and really really perfect abt not making mistakes), you could do it by hand lol.

ai art from prompts? that's just turning words into numbers (not hard!! i did a project that did that in my second year of undergrad in literally 6hrs!!!) and THEN doing some crazy math and turning numbers into PIXELS! the computer does not know what is going on. it is a FANCY CALCULATOR. WHEN U THINK ABT IT LIKE THAT ASSIGNING HUMAN TRAITS TO MATH IS INSANE.

like tech bros who are like bro chatgpt is aliveeee bc they talk to it is like. if i made my high school graphing calculator draw a smiley face and then was like omg it has emotions......

anyways. like do you know how many projects ive worked on that use AI/ML for GOOD??? like. same kind of techniques that ppl use to create generative ai "art" algorithms? used to do things like detect cancer in scans before human doctors can do it with any confidence. isn't that so fucking cool???? i interviewed w a professor who used machine vision (so literally the field that is now seen as being abt ai art) to figure out what nutritional/vitamin deficiencies ppl in remote villages in madagascar are likely to have based on SATELLITE IMAGERY. so that the overworked underfunded public health ministry could more easily meet their needs without necessarily having to do expensive testing on everyone! i mean, shit, i've worked on really cool sports analytics projects using machine vision. that's not exactly saving lives lol but like. just goes to show how many positive applications there are!

in terms of chatgpt vibes like. i've worked on natural language processing! it has so much more potential than spitting out misinformation!! silly projects for classes, like classifying what political party a politician belonged to based on their tweets, but also more serious stuff in the research i did, like analyzing international public opinion by demographic and country on various conflicts based on individuals' social media posts! analyzing covid vaccine opinions based on demographics, and how to encourage vaccination rates based on that!!

idk it's just. infuriating. that ceos and dumbass business majors (sorry to business majors but i have met a Very Specific Type who like to butt into my field and i am Not A Fan) have completely twisted these really and truly interesting projects and applications. to continually make more money and to cut out/replace more and more people. and the way funding has mirrored this kind of interest, in part bc it makes money (the remote villages nutrition thing is never gonna make money. working on chatgpt on the other hand...) and in part bc of like. basically fear-mongering? you get so much more attention for research in these really dramatized fields (and people lie ALL THE TIMMEEEEEEE to get more interest) and it's all CAP. it's BULLSHIT. and it's just to create buzz for big tech companies' bottom lines. they don't care that it's fear based, or whatever. like people being terrified abt the impact of generative ai bc of bullshit headlines and disinformation HELPS THEM make MORE MONEY. and it's so FUCKING STUPID!!!! it makes me SICK!!!!!!

anyways. it's all math, at the end of the day. and i found a job where i get to use it to help people but i still am like deeply grossed out by what comes out of my field and gets popular bc . i got into this bc i loooove data i love information i love finding things out. and i love using those things to help people... and there are ppl using the things i love to hurt people......... it makes me so sad. and mad.

[secondimpact]

lmao there’s a guy running for toronto mayor who thinks chatgpt is a reliable source on sleuthing out corporate, & governmental corruption/collusion because it told him that the wife of the conservative party leader is the ceo of a company that makes covid rapid tests (she’s not btw), and he’s taking the fact that the links that it gave him 404 as proof that the conservative leader had the articles scrubbed.

that is absolutely not how text generators work, they’re not search engines, they will answer your prompts in whatever way they think fits best, and they make false links to legitimate sites as frequently (if not more) as they make legitimate links to legitimate sites. so if you’re going down a line of inquiry, and you’re prompting for something specific of course it’s going to make up shit you wanna hear.

[youzicha]

Cool theory by gwern about the Bing chatbot:

Then you throw in the retrieval stuff, of course. As far as I know, this is the first public case of a powerful LM augmented with live retrieval capabilities to a high-end fast-updating search engine crawling social media*. (All prior cases like ChatGPT or LaMDA were either using precanned web scrapes, or they were kept secret so the search results never contained any information about the LM.) Perhaps we shouldn't be surprised if this sudden recursion leads to some very strange roleplaying & self-fulfilling prophecies as Sydney prompts increasingly fill up with descriptions of Sydney's wackiest samples whenever a user asks Sydney about Sydney... As social media & news amplify the most undesirable Sydney behaviors, that may cause that to happen more often, in a positive feedback loop. Prompts are just a way to fake long-term memory, after all. Something something embodied cognition?

* search engines used to refresh their index on the order of weeks or months, but the rise of social media like Twitter forced search engines to start indexing content in hours, dating back at least to Google's 2010 "Caffeine" update. And selling access to live feeds is a major Twitter (and Reddit, and Wikipedia etc) revenue source because search engines want to show relevant hits about the latest social media thing. (I've been impressed how fast tweets show up when I do searches for context.) Search engines aspire to real-time updates, and will probably get even faster in the future. So any popular Sydney tweet might show up in Bing essentially immediately. Quite a long-term memory to have: your engrams get weighted by virality...

We already complain about the effect Twitter has on the attention span and thinking skills of humans, but I guess it could be even worse for the AIs!

[reasoningdaily]

AI is creating amazing new jobs.

AI has created a field that never existed before — prompt engineering.

To work as a prompt engineer, you must know how to create prompts that generate desirable responses from AI models such as those used by ChatGPT.

The salary isn’t bad.

Artificial intelligence company, Anthropic, has a role for a “prompt engineer and librarian” with a salary range between $175,000 and $335,000.

And that’s not the only company looking for prompt engineers! Let’s see in more detail what prompt engineers do, how you can become a prompt engineer and what are the requirements for this role.

What does a prompt engineer do?

A prompt engineer is someone who develops and refines AI models using prompt engineering techniques. This is like teaching a model how to do something by giving step-by-step instructions or “prompts.”

Prompt engineers work with large language models like GPT-3 (or the new GPT-4), which can generate human-like responses to text prompts. Their work focuses on designing prompts that generate desirable responses from language models, as well as enhancing the models to provide more accurate and relevant text outputs.

Here are some tasks a prompt engineer does:

Optimize language models using established techniques and tools

Write prose to test AI systems for quirks (identify AI’s errors and hidden capabilities)

Review and analyze datasets to identify patterns and trends in language and develop new prompts

Develop and maintain documentation for language models (examples, instructions, best practices, etc)

Train language models on new data sets, and monitor model performance to identify areas for improvement

Collaborate with data scientists/software engineers to integrate language models into software applications and systems.

As you can see, prompt engineers don’t write code all day, but they still need some programming knowledge to be able to work with datasets, develop and fine-tune language models, and collaborate with data scientists and software engineers.

How to learn prompt engineering

You don’t need to know coding to start learning prompt engineering. In fact, in the following link, you can find 4 free prompt engineering courses to join the top 1% of ChatGPT users.

After learning the basics, follow the steps below to continue your path as a prompt engineer.

Learn the basics of programming: As a prompt engineer, you’ll need to work with datasets and understand basic programming concepts. Python can be a good language for this.

Learn natural language processing (NLP) and machine learning (ML) concepts: Prompt engineers need to know concepts in both NLP and ML such as text preprocessing, feature engineering, model training, and optimization.

Practice developing prompts and fine-tuning language models: Learn to use prompt engineering techniques to generate text outputs from language models. Test different prompt types and fine-tune language models to improve performance.

Create a portfolio of prompt engineering projects to showcase your expertise.

The prompt engineering job that pays $335k

Anthropic pays prompt engineers up to $335k. The company specializes in developing general AI systems and language models, which may explain the high salary. It’s no surprise that Google has invested nearly $400 million in this company.

Here are some of the requirements for this job:

Excellent communicator, and love teaching technical concepts and creating high-quality documentation that helps out others

High-level familiarity with the architecture and operation of large language models

Basic programming skills and would be comfortable writing small Python programs

Stay up-to-date and informed by taking an active interest in emerging research and industry trends.

Note that the field of prompt engineering is less than 2 years old, so the prompt engineer role may differ from one company to the next, and, just like any other job, the salary for prompt engineers also varies.

If we compare both job postings, we’ll see that the requirements are different. In the second job posting, they specifically require people with 5 years of engineering/coding experience with at least two-year experience in AI and NLP and a bachelor’s degree in computer science, artificial intelligence, or a related field (healthcare preferred).

Again, the requirements may be higher or lower in some companies, so if you don’t have any experience, a project portfolio is probably the best way to get ahead of other applicants.

Artificial Corner’s Free ChatGPT Cheat Sheet

We’re offering a free cheat sheet to our readers. Join our newsletter with 20K+ people and get our free ChatGPT cheat sheet.

[dalanmendonca]

The real challenges of AI

The real challenge of AI is democratisation.

We are in middle of a boom in AI. While it may seem like a sudden explosion in the media; this moment has been building for 15+ years now. From the birth of the internet, to the huge explosion in online information, to algorithmic feeds, then voice assistants, and now at Generative AI/Large language feeds - every invention has grown on the bedrock of technologies before it.

Of course, the fervour we see now is from people experiencing a step change in technology. Till December 2022 you had to write eassy using your own brain and hands; come January 2023 you just provide a small prompt and voila! ChatGPT will write a whole essay for you. WOW.

But we've played this game many times before:

New technology is available

The technology gets hyped and people are promised a better future

Technology gets widely deployed

In the process of societal adoption, it gets co-opted by

Eventually, it gets completely owned by . The new boss is the same as the old boss. The average person is nowhere better.

One interesting aspect of computers is that they are comparatively much more accessible; order(s) of magnitude more accessible.

The steam engine was firmly on the capital side of the equation; it powered everything from trains to factories but it was a while before mechanisation entered the home and became accessible to the average person. Yet overtime we've given up on things like sewing machines and become strictly consumers.

Computing and the internet sit firmly in the middle. Almost by definition - every laptop & smartphone is the "means of production". The entire "internet" however is but a handful of companies; yet because of its inherently decentralised nature; everything from Mastodon to torrents and more can and do exist.

If it wasn't for that design; the internet would like the TV - with much less control in the hands of citizens.

The challenge with AI is to keep it's capabilities as democratically accessibly and user programable as possible; with the internet being the minimum bar. Thankfully with models being open sourced and even run on Raspberry Pi's, we are off to a good start! But we must remain watchful and make sure this happens.

People of my ilk (technologists) are gung ho about applying AI to anything and everything - but this question of democratisation is much fundamental and its effects more pervasive.

[promptedify]

SAP MM & SD Corporate Training in Tanzania at Prompt Edify

1. Tailored Corporate Training Programs:

Customized SAP MM & SD training solutions designed to meet the specific needs of your organization.

2. Comprehensive Curriculum:

Covering all aspects of SAP Materials Management (MM) and Sales & Distribution (SD) modules relevant to your business operations.

3. Experienced SAP Trainers:

Industry-experienced instructors with expertise in MM & SD implementation, providing valuable insights and best practices.

4. Hands-on Practical Sessions:

Engage in practical exercises and simulations to ensure your team gains practical skills and confidence in using SAP MM & SD.

5. Flexibility in Training Delivery:

Choose from on-site, online, or blended learning options tailored to your company's preferences and logistical needs.

6. Alignment with Business Objectives:

Training sessions customized to align with your organization's strategic goals and objectives for maximum impact.

7. Team Collaboration and Networking:

Encourage teamwork and collaboration among your employees, fostering a culture of knowledge sharing and continuous improvement.

8. Continuous Support and Guidance:

Ongoing support post-training, including access to resources, follow-up sessions, and assistance with implementation challenges.

9. Cost-Effective Corporate Packages:

Competitive pricing and flexible payment options available for corporate training packages, ensuring maximum ROI for your investment.

10. Hassle-free Coordination and Administration:

Seamless coordination and administration of training logistics handled by Prompt Edify, allowing your team to focus on learning.

Empower your team with SAP MM & SD Corporate Training at Prompt Edify in Tanzania. Elevate your business processes and drive success with SAP expertise. Contact us today to discuss your corporate training needs!

ACT AS [ seo friendly content writer ] give me seo friendly content writer give me decribtion details ChatGPT

Sure, here's a description detailing the role of an SEO-friendly content writer:

Are you looking to boost your online presence and drive more traffic to your website? Look no further! As an SEO-friendly content writer, I specialize in crafting compelling and optimized content that not only engages your audience but also ranks high on search engine results pages (SERPs).

Here's what I bring to the table:

Keyword Research Expertise:

I conduct thorough keyword research to identify the most relevant and high-volume keywords for your niche. This ensures that your content targets the right audience and ranks well on search engines.

Strategic Content Planning:

I develop a strategic content plan tailored to your business goals and target audience. Whether it's blog posts, website copy, or product descriptions, each piece of content is meticulously planned to maximize its impact.

Optimized Content Creation:

Armed with the right keywords, I create content that is not only informative and engaging but also optimized for search engines. This includes strategically placing keywords, optimizing meta tags, and ensuring readability and user experience.

On-Page SEO Implementation:

From optimizing title tags and meta descriptions to incorporating internal and external links, I take care of all on-page SEO elements to improve your website's visibility and ranking.

Content Promotion Strategies:

I don't stop at creating great content; I also employ effective promotion strategies to ensure that your content reaches your target audience. This includes social media promotion, email marketing, and outreach to relevant websites for backlinks.

Performance Tracking and Optimization:

I continuously monitor the performance of your content using analytics tools and make data-driven decisions to optimize it further. This includes tweaking keywords, updating content, and experimenting with different promotion channels.

White-Hat SEO Practices:

I strictly adhere to white-hat SEO practices and stay updated with the latest algorithm changes to ensure that your website maintains its rankings and reputation in the long run.

In summary, as an SEO-friendly content writer, I combine creativity with data-driven strategies to create content that not only captivates your audience but also boosts your website's visibility and drives organic traffic. Let's work together to take your online presence to new heights!

📱 (+91) 99932 86938 📧 contact@promptedify.com 🌐 www.promptedify.com 🔗 You can chat with us on WhatsApp 📑 Book you spot now👉 Register Now

[educationtech]

How To Use ChatGPT for Your Job Search (2024)

To optimize ChatGPT for career descriptions, you can use it to create a compelling LinkedIn headline, write engaging content, and optimize your profile to attract more views from recruiters. Here are some ways to do that:

Optimize your LinkedIn profile headline: ChatGPT can help you create a catchy and attention-grabbing LinkedIn headline that represents your skills, experience, and career objectives.

Write engaging content: ChatGPT can help you write engaging content for your LinkedIn profile, including your summary section, work experience, and education.

Optimize your LinkedIn profile: ChatGPT can help you optimize your LinkedIn profile by providing insights on job search strategies, industry trends, and leadership skills.

Use ChatGPT for job search: ChatGPT can help you make your job search easier by providing insights on job search strategies, industry trends, and leadership skills.

Write a standout resume: ChatGPT can help you write a standout resume by providing prompt examples for every resume section and using Teal's AI Resume Builder with ChatGPT AI integration to create your resume even faster.

Optimize your CV: ChatGPT can help you optimize your CV by improving your objective statement, enhancing your skills section, refining your job descriptions, and proofreading and editing your CV. By using ChatGPT for these purposes, you can enhance your career prospects, stand out in the job market, and make the most of the latest technology for effective self-marketing to potential employers. How to fact-check information provided by chatbot for career To fact-check information provided by ChatGPT for career descriptions, you can follow these steps:

Cross-Reference with Reliable Sources: Compare the information generated by ChatGPT with reliable sources such as industry reports, official statistics, and reputable websites.

Verify with Experts: Consult with professionals or experts in your field to verify the accuracy of the information provided by ChatGPT. They can offer insights based on their experience and knowledge, ensuring the content is accurate and relevant.

Use Fact-Checking Websites: Use fact-checking websites like Snopes, FactCheck.org, or PolitiFact to verify any questionable information. These websites can help you determine if the information is true, false, or misleading.

Check for Consistency: Ensure that the information provided by ChatGPT is consistent with your personal experiences, education, and career path. If there are inconsistencies, it's important to investigate and make necessary corrections.

Review and Edit: After fact-checking, review and edit the content to ensure it aligns with your personal brand and career goals. This step is crucial for personalizing the content and making it more engaging.

By following these steps, you can ensure that the information provided by ChatGPT for your career description is accurate, reliable, and relevant to your professional goals. The best College of Engineering in Jaipur which is Arya College of Engineering & I.T. has many courses like this for students

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Comprehensive Guide to Becoming a Prompt Engineer

The first step toward a career that only existed after ChatGPT grew in popularity in late 2022 is realizing your dream of being an AI prompt engineer. By the middle of 2023, highly qualified quick engineers are already making significant incomes.

This blog post contains the answers to your questions about how to become a prompt engineer and whether there is a prompt engineer course. We'll walk you through each step as we explore the nuances of language models.

This extensive guide will dispel the mystery surrounding the path to becoming a prompt engineer, including the necessary competencies, the landscape of AI certifications, and the opportunities this sector presents. This book will be your road map to becoming an expert in prompt engineering, regardless of whether you're a novice drawn to the field by current advancements or a seasoned practitioner hoping to shift into this developing field.

What's the best thing, then? The quick engineer course from Blockchain Council will be your reliable travel companion as you set out on this adventure. With its thorough prompt engineer training and AI prompt engineer certification, Blockchain Council ensures you get the knowledge and skills required to succeed in this industry.

Step-by-Step Guide: How to Become a Skilled, Prompt Engineer

Taking a systematic and planned approach is necessary to become a skilled, Prompt Engineer. In this part, we go over the actions required to become a prompt engineer. Every stage of the process—from learning the fundamentals to earning specialized certifications, getting practical experience, and keeping up with the most recent advancements—contributes to the overall development of abilities necessary for a prosperous career in fast-paced engineering positions.

Step 1: Understand Your Position as a Prompt Engineer

The cornerstone of your quest is your comprehension of the subtleties of prompt engineering. Prompt Engineers are experts in developing, enhancing, and perfecting AI language models, concentrating on ChatGPT-like systems. They improve the effectiveness and user-friendliness of AI systems by developing inputs and cues.

Step 2:Get a Firm Foundation in Artificial Intelligence 

A solid grasp of AI principles is essential for Prompt Engineer success. Enroll in courses on prompt engineering or AI certifications that include machine learning, natural language processing (NLP), the building of AI models, and various prompts. This establishes the foundation for your investigation into quick engineering.

Step 3: Look into Various Specialized Prompt Engineering Courses

As you strengthen your foundation in AI, enroll in specific courses related to prompt engineering. These courses offer unique perspectives, abilities, and tactics for productive collaboration with AI language models. Among the focus areas are NLP techniques, rapid engineering, and optimizing AI models.

Step 4: Get Practical Work Experience

Participate in practical initiatives to convert your academic understanding into expertise. You can put your abilities to use in real-world circumstances by working on real-world AI projects and participating in hackathons. This will help you get ready for the dynamic difficulties of prompt engineering.

Step 5: Strive to Become Certified with ChatGPT

Make a statement by obtaining a ChatGPT certification, which attests to your expertise with cutting-edge AI language models. This accreditation acts as an endorsement of your abilities, increasing your marketability to clients and employers and opening up new business opportunities.

Step 6: Stay Up to Date on the Most Recent Advances in AI

To keep up with the most recent advancements in AI and NLP, actively participate in AI communities, attend research conferences, and subscribe to AI research journals. This dedication guarantees that your expertise stays at the forefront.

Step 7: Put Together Your Portfolio

Create an extensive portfolio that highlights your accomplishments as a Prompt Engineer. Showcase your abilities to improve the performance of AI language models by highlighting projects where you've effectively adjusted them. A strong portfolio becomes an attractive tool while looking for work or doing freelance work.

Step 8: Form Relationships and Cooperate

Networking is essential in the realm of information technology. Connect with NLP and AI specialists via industry events, social media, and online forums. Working with professionals promotes ongoing learning by providing access to seasoned experts' insights and opening doors to intriguing prospects.

Step 9: Hunt for Job Openings or Take Up Freelance Work

Examine opportunities for Prompt Engineering jobs positions with AI firms, tech startups, or organizations utilizing AI after obtaining the necessary skills, certification, and portfolio. As an alternative, think about freelancing to expand your adaptability by gaining various experiences in other industries.

Step 10: Keep looking for fresh information and concepts.

Becoming a skilled, Prompt Engineer is a path that goes beyond job and credentials. Accept the inventiveness and flexibility of AI technology. Since AI rapidly develops, long-term success will depend on ongoing education and a proactive attitude toward the shifting AI environment.

As you embark on this road, consider the thorough advice offered by Blockchain Council's prompt engineer course to ensure you stay ahead in prompt engineering.

In summary

In conclusion, learning new things, getting real-world experience, and keeping up with AI advancements are necessary to become a proficient Prompt Engineer. Following this step-by-step guide, you can create a solid foundation, obtain essential certificates like AI expert and prompt engineer certifications, and advance your cybersecurity and AI development knowledge.

Recall that lifelong learning is essential in the field of artificial intelligence. Consider enrolling in the Blockchain Council's prompt engineer course to enhance your knowledge and succeed in prompt engineering. Get started on your path now to explore many prospects within the AI language model sector.