10 Ultimate AI Cheat Sheet - Part 5

20 AI SEO TOOLS TO BOOST YOUR CONTENT

MARKETING

Hubspot AI Tools

Efficiently create, update, and optimize SEO content with seamless AI-assisted workflows.

INK

Enhances SEO with keyword clustering, competitive analysis, and data integration tools

SE Ranking

Offers AI-powered tools for content writing, SEO insights, and monitoring Google updates

Quickly creates engaging videos from scripts to repurpose content and boost website ROI

Generates data-driven content briefs and identifies SEO opportunities to outperform competitors.

AI Search Grader

Analyze your brand's visibility in AI search engines like ChatGPT to enhance awareness.

Jasper

Creates high-quality, branded content across platforms with an intuitive campaign dashboard

Outranking

Transforms keyword research into optimized workflows and a prioritized content calendar

Optimizes site performance with automated caching, compression, and code enhancements

Boosts SEO by automating accurate, context-driven internal link suggestions on WordPress.

Alli AI

Simplifies website optimization with bulk SEO, automated testing, and CMS compatibility

RankIQ

Boosts blogging ROI with low-competition keywords, quick content updates, and SEO tools Paraphrasing

Repurpose webinars and audio with clear, accurate paraphrasing and word definitions

Automates content briefs, multilingual writing, and SERP-based optimization for top rankings

NeuralText

Integrates SEO, keyword research, and AI copywriting for optimized, user-friendly content

Frase

Neuron Writer

Combines NLP-driven content writing, competitor analysis, and SEO optimization tools

Scalenut

Provides AI tools for keyword planning, SERP analysis, and real-time content optimization

Market Muse

Uses topic modeling and gap analysis to create optimized, competitive content strategies

Streamlines SEO content creation with tools for briefs, keyword insights, and question targeting.

Surge Graph

AI tools for long-form content creation, keyword analysis, and content optimization to maximize SEO rankings quickly.

2025 AI ENGINEER MASTERY GUIDE

YOUR STEP-BY-STEP PATH TO AI EXPERTISE

Prerequisites

Required

Skills:

Basic coding knowledge (Python preferred)

Foundational math skills: algebra, calculus, and probability

AI Engineer = Data Scientist + Software engineer

Core Skills for AI Engineers:

Computer Science Fundamentals.

Data Analysis

Machine Learning

NLP & Computer Vision

MLOps

Topics:

Tips:

Tool Skills: Python, SQL Git, GitHub Scikit-learn, TensorFlow, PyTorch.

Step 2: Learn Python Basics

Python Basics: Variables, loops, data structures (lists, dictionaries, sets)

Functions and Lambda Expressions

Modules: NumPy, Pandas, Matplotlib for data handling and visualization

Learning Resources:

Corey Schafer’s Python Tutorials (YouTube)

FreeCodeCamp Python Tutorials

Automate the Boring Stuff with Python (Book)

Step 3: Version Control (Git, GitHub)

Topics:

Setting up repositories and branches

Git basics: add, commit, push, merge.

Learning Resources:

Git & GitHub Crash Course

Atlassian Git Tutorials

GitHub Crash Course by Traversy Media (YouTube)

Step 6: Math & Statistics for AI

Topics:

Descriptive and inferential statistics

Linear Algebra: Matrices, Eigenvalues Probability distributions, Bayes Theorem Learning Resources: Khan Academy: Statistics and Probability 3Blue1Brown YouTube Channel Introduction to Statistical Learning (Book)

Step 8: NLP and Computer Vision

NLP Topics:

Text processing, tokenization. BERT, GPT, and Transformers

Libraries: Hugging Face, Spacy, NLTK. Computer Vision Topics: Image processing, object detection (YOLO, SSD) Neural Networks: CNNs

Learning Resources: NLP Playlist by The AI Epiphany Stanford CS231n (Computer Vision)

Topics:

Step 0: Protect Yourself from Scams❌

Beware of promises for instant results; learning AI requires consistent effort

Verify the credibility of courses and mentors

Research industry trends and demands before starting

Key Resource:

Snyk Blog: Scam Awareness in AI Education

Step 1: Computer Science Fundamentals

Topics:

Data representation, binary systems

Basics of algorithms and computer networks

Problem-solving techniques

Learning Resources:

CS50 by Harvard Brilliant org: Fundamentals of Computer Science

Khan Academy: Introduction to Computer Programming

Step 4: Data Structures and Algorithms (DSA)

Topics:

Arrays, Linked Lists, Stacks, Queues

Sorting: Bubble, Merge, Quick Sort. Graphs and Trees

Learning Resources: FreeCodeCamp’s DSA Playlist

LeetCode for Practical Exercises

Data Structures by MIT OpenCourseWare

Step 7: Machine Learning

Preprocessing: Handling missing data, normalization, encoding Supervised Learning: Linear Regression, Decision Trees Unsupervised Learning: Clustering, PCA Evaluation Metrics: Confusion Matrix, Precision, Recall Learning Resources: Hands-On Machine Learning by Aurélien Géron (Book)

Andrew Ng’s ML Course (Coursera) Kaggle Datasets for ML Projects

Step 9: MLOps

Topics:

CI/CD pipelines Model deployment (AWS, Docker, Kubernetes)

Monitoring model performance

Learning Resources: Full Stack Deep Learning Tutorials FastAPI and Docker for Deployment

Step 5: SQL and Databases

Topics:

Basic queries: SELECT, WHERE, GROUP BY. Advanced concepts: Joins, subqueries, stored procedures

Learning Resources: Khan Academy SQL Mode Analytics SQL Tutorial

Additional Platforms and Tools

YouTube Channels: Sentdex, StatQuest, 3Blue1Brown Online Courses: edX, Coursera, Udemy

Interactive Coding Platforms: Kaggle, HackerRank, DataCamp

Step 10: Deep Learning

Topics:

Neural Networks: Forward/Backward Propagation Architectures: CNNs, RNNs, Transformers.

Learning Resources: Deep Learning Specialization by Andrew Ng (Coursera) TensorFlow/Keras Tutorials

FREE AI Learning Resources FREE AI Learning Resources

YouTube Channels for AI ��

Analytics

Websites for Free AI Courses ��

classcentral.com: Aggregated free AI course listings mygreatlearning.com: AI courses with certifications udacity.com: Advanced AI nanodegree programs ai.google: Official Google AI learning resources edx.org: AI courses from top universities freecodecamp.org: Free coding and AI resources pll.harvard.edu: Harvard’s free AI and data courses deeplearning.ai: Industry-standard AI courses

Top Courses from Google ��

Introduction to TensorFlow: Learn AI, ML, and DL basics.

Natural Language Processing with TensorFlow: NLP techniques.

AI for Everyone: Accessible AI concepts. Fundamentals of Reinforcement Learning: RL fundamentals.

Building TensorFlow Lite Applications: Mobile AI deployment.

Generative Adversarial Networks (GANs): Create synthetic data.

Machine Learning Crash Course: Hands-on ML basics.

Elements of AI: Core AI principles and applications.

Blog Websites for AI ��

aifire.co: AI news updates and practical AI tutorials. machinelearningisfun.com: Simplified AI concepts. kdnuggets.com: AI and machine learning news. towardsdatascience.com: Practical AI tutorials. machinelearningmastery.com: Hands-on ML guides. openai.com/blog: Updates from OpenAI. distill.pub: Interactive AI research. analyticsvidhya.com: Data science tutorials. ai googleblog com: Google AI research updates fastml com: Quick ML tutorials towardsai.net: AI news and insights

Websites for Datasets ��

OpenML: Open-source datasets for machine learning

Microsoft Azure Open Datasets: Trusted datasets for AI projects

Google Cloud AI Platform Datasets: Scalable datasets for AI applications

UCI Machine Learning Repository: A hub for classic ML datasets

Papers with Code: Benchmarked datasets with AI implementations

Amazon SageMaker Open Data Registry: Open data for ML and AI

Kaggle: Rich community and extensive datasets

MachineHack Datasets: Practice datasets for AI competitions

Hugging Face Datasets: Comprehensive NLP datasets

OpenMLDB: Efficient datasets for machine learning

Top Courses from Microsoft ��

Building AI Solutions on Azure: Azure AI fundamentals

Machine Learning for Beginners: Introductory ML concepts

AI for Beginners: Basics of artificial intelligence

Azure Machine Learning Essentials: Azure ML workflows

Introduction to Artificial Intelligence: Core AI foundations

Transform Your Business with AI: Business applications of AI

Responsible AI: Ethics and safety in AI

Azure AI Fundamentals: Comprehensive Azure AI tools

Career Essentials in Generative AI: Tools for professional AI skills

Vidhya

Alex The Analyst Lex Fridman Matt Wolfee Corey Schafer

3Blue1Brown Sentdex StatQuest with Josh Starmer

Two Minute Papers Dirk Zee

How to Make YouTube-Grade Animation with Free AI

Generate a Script with ChatGPT

Use ChatGPT to create a story script based on your chosen theme or topic.

Generate AI Animated Photos

Use FlexClip's AI image generator to create animated pictures that replace non-animated stock photos.

Replace Resources with Animated Videos

Import your video clips into FlexClip, replacing static background resources with the animated visuals you created.

Create an AI Video

Utilize FlexClip's AI textto-video tool to transform the script into a video with subtitles.

Animate the Pictures

Sign up for Runway Gen-2 and upload animated pictures from FlexClip to generate full animated videos in your desired style.

Export and Share

Export the completed AIgenerated video and share it on YouTube or social media. Create a short link to promote your content efficiently.

Pro Tip

Use FlexClip's AI textto-speech feature to add natural-sounding narration in multiple languages and voices. Add Voiceover

Experiment with different AI tools for creativity and quality improvement, including FlexClip's additional features for effects and transitions.

Land Your First Remote Job

UseChatGPTtoanalyzeyourstrengths:

"I want to identify my strongest skills for remote jobs. Analyze my interests, past work, hobbies, or education and suggest relevant skills for remote work." Select1–2skillsthatalignwithyourinterests andmarketneeds

Use tools like Canva and Zety for AI-powered resume templates Optimize your CV for remote jobs with ChatGPT: "Here’s my CV draft Optimize it for [job role] using keywords relevant to remote work"

AIFollow-UpTools:

ChatGPT:Generate politefollow-upemails orLinkedInmessages: "Writeafollow-upemailfor ajobIappliedtoasa[job title]twodaysago" BoomerangforGmail: ScheduleAI-optimized follow-upemails.

Steps to Follow: Search job boards regularly Use AI tools to write personalized pitches.

ChatGPT Prompt: "Write a pitch for a remote content writing role focusing on SEO for small businesses" Goal: Apply to 10+ job postings

Sendfollow-upmessagesfor applicationssubmittedonDay5 UseLinkedIntoexpressinterestand connectwithjobposters

Spend 3–4 hours improving your skills using AI tools.

Use ChatGPT for customized tutorials

Pro Tip: Join skill-specific communities on Reddit, Discord, or Facebook for guidance

Useplatformstoshowcaseyourwork: Behance,Notion,GoogleDrivefolder (simple,cleansetup)

Showcase 2–3relevantprojects(realor practicework)

Send LinkedIn connection requests to recruiters and professionals

Share your services on social platforms: LinkedIn, Twitter, and Facebook

ChatGPT Copyai

JasperAI

TOP 25 AI TOOLS USED IN TOP 25 AI TOOLS USED IN DATA ANALYTICS DATA ANALYTICS

EVERY REMOTE WORKER SHOULD HAVE TOP FREE AI TOOLS

CHATGPT

AI chatbot for task assistance and natural language interactions

OTTER AI

AI-powered transcription tool for notetaking and efficient meeting summaries

ZAPIER CANVA

Workflow automation by connecting apps and services using AI-driven suggestions

GRAMMARLY

Writing assistant that enhances grammar, clarity, and tone.

NOTION AI

Workspace organizer with AI tools for brainstorming, writing, and planning

CALENDLY

AI-powered scheduling assistant for seamless meeting coordination across time zones.

ZOOM

AI-driven video conferencing platform with tools for collaboration and meeting enhancement.

ASANA

AI-enhanced project management software for organizing and tracking team tasks

AI-enhanced graphic design platform for creating visual content effortlessly.

KRISP

Noise-canceling AI tool for crystal-clear audio during calls and recordings.

LOOM

Video messaging platform with AI tools for quick and professional updates

TRELLO

Visual project management tool with AI to enhance task organization and team collaboration.

SLACK

Team communication hub with AI features for workflow and productivity improvements.

MIRO

Visual collaboration platform with AI tools for brainstorming, ideation, and project planning

TheBest80AItools for2025

Explained in 8 Steps Explained in 8 Steps

Problem Definition

Identify the problem or task to be solved. Define the desired outcome and performance metrics.

Data Collection and Preparation

Collect relevant data. Clean, preprocess, and annotate the data. Split the data into training, validation, and test sets.

Model Selection and Algorithm Development

Choose an appropriate AI technique

Select or develop a suitable algorithm or model architecture

Configure model parameters and hyperparameters.

Model Evaluation

Test the trained model on unseen data. Assess performance using predefined metrics. Identify areas for improvement or potential biases

Model Development

Integrate the trained model into the target application. Monitor model performance in real-world scenarios.

Update the model with new data or techniques as needed.

Model Training

Feed the training data into the model. Adjust model weights to minimize the loss function. Monitor model performance using validation data.

Model Fine-tuning and Optimization

Adjust hyperparameters or model architecture

Perform feature engineering or data augmentation. Retrain the model and evaluate performance iteratively.

Ethical Considerations

Ensure AI system’s fairness, accountability, and transparency

Address potential biases and unintended consequences

Follow data privacy and security guidelines