The Ultimate Drawing Course - Beginner to Advanced

The Ultimate Digital Painting Course - Beginner to Advanced

Street Coder, Video Edition [O’Reilly]

Machine Learning in JS [FrontendMasters]

Design Systems with Storybook, v2 [FrontendMasters]

Figma for Developers, v2 [FrontendMasters]

The JavaScript Bible - JavaScript Bootcamp

Udemy - AWS CDK with Python Step by Step

Namaste Frontend System Design

TypeScript Simplified ( Web dev simplified )

Next.js Projects: Build an Issue Tracker ( Code With Mosh)

Nginx - Beginner to Advanced

Discover, Validate & Launch New Business Ideas with ChatGPT

Flutterflow / Firebase 2023 (Tinder clone)

Three.js Bootcamp: Zero to Mastery

Microservices and Distributed Systems 2023 (Amigoscode)

Zero to Hero Java SpringBoot & JPA Mastery with Real Project

Testing React with Jest and React Testing Library (RTL) 2023

Spring Boot Microservices and Spring Cloud. Build & Deploy.

100 Days of JavaScript - Udemy

Ultimate Next 13 Course ( JsMastery Pro )

Unity Bootcamp: 3D Game Development (Zero To Mastery)

Flutterflow Crash Course For Beginners. Build Your First App

Learn Flutterflow. Build a Chat GPT Clone App

Build a Chat application using WebSockets and Channels in this section. We'll cover 0 to deployment.
<h3 id="recommendedexperience">Recommended Experience:</h3>
<ul>
<li>Strong Understanding of Django and Core Concepts</li>
<li>Basic JavaScript</li>
<li>Git (for setting up the project)</li>
</ul>
1 - Setup Project 2 - Non-Realtime App with Django only 3 - Setup Django Channels 4 - Websocket Routing 5 - Consumer in Python &amp; WebSocket API in JavaScript 6 - Accept WebSocket Connection 7 - Send &amp; Receive Messages via WebSockets 8 - Async Consumer 9 - WebSocket Groups 10 - The User in a Consumer 11 - Display Messages 12 - Save Chats in the Database 13 - Broadcast Message to Group 14 - Broadcast Utility 15 - Delayed Broadcast Message 16 - Deploy to Heroku
Workers &amp; Channels
Picking up from the WebSockets &amp; Channels section we'll show you how to build a worker process in Channels v2 so you can offload tasks from the main Django thread.
1 - Task Consumer 2 - Synchronous Trigger 3 - Test Run Worker Process 4 - Implement Worker Trigger 5 - Complete the Consumer

Chat x Channels 🔥

Chat x Channels - Coding for entrepreneurs

Machine Learning is one of the most fascinating topics in programming today. It's applications are far reaching and has quickly became an essential attribute for nearly all software projects.
This ongoing course will teach you how to do machine learning in the most practical way possible.
<img src="https://static.codingforentrepreneurs.com/media/series/cc-machine-learning/sections/python-text-classification/20ce2dd4-a646-43fe-adb0-7a562ea12.jpg" alt="" width="1200" height="630" />
<h4 class="text-lg text-center">Python for Text Classification</h4>
<div class="markdown-preview-container-40 py-3 mb-3 mx-2 space-y-2">
<div class="cfe-markdown-render">
How does a spam filter work? How do you decide sentiment on a line of text? How do you categorize news headlines automatically?
These questions are all answered through the concepts of Machine Learning &amp; Text Classification.
Natural language of all kinds has nuances that a computer has trouble picking up. Think about the simple sentence:
"While I ate, the dog and I laughed."
"While I ate the dog and I laughed."
Same words but one single comma and the entire context changes. This simple example sheds light on how difficult it is to get a computer to understand all the complexities of human language.
This section is dedicated to helping you parse through text and make more sense of it so you can make it actionable.
<a href="https://github.com/codingforentrepreneurs/Python-for-Text-Classification">Github Repo</a>
1 - Intro 2 - Sublime Text &amp; Jupyter Notebooks 3 - Initialize Virtual Environment with Pipenv 4 - Bag of Words 5 - One Hot Array 6 - Bag of Words Function 7 - One Hot Array Function 8 - One Hot Array Back to Text 9 - Bag of Words with External Data File 10 - One Hot Array with External Data 11 - Training Data and Labels as Numpy Arrays 12 - Train and Predict with Sklearn SVM 13 - Text Prediction Recap 14 - Reusable Sklearn Classifier 15 - Missing BOW 16 - Pickles 17 - Good Data In, Good Data Out 18 - Dataset Resources 19 - Grab and Parse Dataset 20 - Prepare Training Model for Spam + Not Spam 21 - Train Spam Classifier 22 - Clean and Predict 23 - Scoring Classifier Accuracy 24 - One Hot Encoding Classification Recap 25 - Preprocessing with a Keras Tokenizer 26 - Pad Sequences 27 - Convert Our Text Data into Sequences 28 - Labels and LabelEncoder 29 - Reusable Text-Label Utility 30 - Split Training and Validation Data 31 - Tokenized Text Classifier 32 - Cross Validation 33 - Sensitivity vs Specificity
</div>
</div>

Machine Learning - Coding for Entrepreneurs

<h2>Courses in this path</h2>
<div class="row border-top difficulty-container active">
<div class="difficulty-header">
Beginner -&nbsp;Experience the machine learning workflow as implemented in scikit-learn, and use that workflow to build simple classification, regression, and clustering models.
1. Building Your First scikit-learn Solution
2. Building Classification Models with scikit-learn
3. Building Regression Models with scikit-learn
4. Building Clustering Models with scikit-learn
Intermediate -&nbsp;Build sophisticated neural network models, apply dimension reduction techniques, and combine model approaches.
1. Building Neural Networks with scikit-learn
2. Reducing Dimensions in Data with scikit-learn
3. Employing Ensemble Methods with scikit-learn
Advanced -&nbsp;Select the appropriate model for your business problem and data, and evaluate the effectiveness of that model.
1. Preparing Data for Modeling with scikit-learn
2. Scaling scikit-learn Solutions
3. Model Evaluation and Selection Using scikit-learn
<div class="path-content-course-items">
<div class="paths-aside-scrollable">
<h3>What you will learn:</h3>
<ul>
<li>Design and implement common machine learning solutions using scikit-learn</li>
<li>Evaluation and validation of scikit-learn machine learning models</li>
</ul>
</div>
<h3>Experience</h3>
<ul>
<li>Data Literacy</li>
<li>Data Analytics Literacy</li>
<li>Statistics</li>
<li>Python programming</li>
</ul>
</div>
</div>
</div>

Building Machine Learning Solutions ❤️‍🔥

Building Machine Learning Solutions with scikit-learn - Pluralsight

Learn Tensorflow 2.0, Deep Learning, Artificial Intelligence, Machine Learning, Neural Networks, Computer Vision, NLP, GANs, and more! Build your own models with Tensorflow, serve models with RESTful API, and deploy on mobile devices. Beginner to expert-level course. Machine Learning and Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!
&nbsp;
<h2>What you'll Learn</h2>
<ul style="list-style-type: circle;">
<li>Artificial Neural Networks (ANNs)/Deep Neural Networks (DNNs)</li>
<li>Anticipate Stock Returns</li>
<li>Time Series Determining</li>
<li>Computer Vision</li>
<li>The most effective method to construct a Deep Reinforcement Learning Stock Exchanging Bot</li>
<li>GANs (Generative Antagonistic Networks)</li>
<li>Recommender Systems</li>
<li>Image Recognition</li>
<li>Convolutional Neural Networks (CNNs)</li>
<li>Recurrent Neural Networks (RNNs)</li>
<li>Utilize Tensorflow Serving to serve your model utilizing a Soothing Programming interface</li>
<li>Utilize Tensorflow Lite to trade your model for portable (Android, iOS) and implanted gadgets</li>
<li>Utilize Tensorflow's Distribution Strategies to parallelize learning</li>
<li>Low-level Tensorflow, inclination tape, and how to fabricate your own custom models</li>
<li>Natural Language Processing (NLP) with Deep Learning</li>
<li>Exhibit Moore's Regulation utilizing Code</li>
<li>Transfer Learning to make cutting edge image classifiers</li>
</ul>
&nbsp;
<h2>Necessities</h2>
Know how to code in Python and Numpy
For the hypothetical parts (discretionary), grasp subsidiaries and likelihood
Depiction
Welcome to Tensorflow 2.0!
&nbsp;
What a thrilling time. It's been almost a long time since Tensorflow was delivered, and the library has developed to its true second rendition.
Tensorflow is Google's library for deep learning and artificial intelligence.
Deep Learning has been liable for a few astounding accomplishments as of late, for example,
Producing delightful, photograph reasonable images of individuals and things that never existed (GANs)
Beating title holders in the system game Go, and complex computer games like CS:GO and Dota 2 (Deep Reinforcement Learning)
Self-driving vehicles (Computer Vision)
Discourse recognition (for example Siri) and machine interpretation (Natural Language Processing)
In any event, making recordings of individuals doing and making statements they never did (DeepFakes - a possibly loathsome utilization of deep learning)
&nbsp;
Tensorflow is the world's most well known library for deep learning, and it's worked by Google, whose parent Letters in order as of late turned into the most money rich organization on the planet (only a couple of days before I composed this). It is the library of decision for some organizations doing artificial intelligence and machine learning.
At the end of the day, to do deep learning, you need to know Tensorflow.
&nbsp;
This course is for novice understudies as far as possible up to master level understudies. How is this possible?
On the off chance that you've quite recently taken my free Numpy essential, then you know all that you really want to bounce right in. We will begin with an extremely essential machine learning models and advance to cutting edge ideas.
En route, you will find out pretty much all of the significant deep learning designs, like Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (succession information).
Current tasks include:
Natural Language Processing (NLP)
Recommender Systems
Transfer Learning for Computer Vision
Generative Antagonistic Networks (GANs)
Deep Reinforcement Learning Stock Exchanging Bot
Regardless of whether you've taken every one of my past courses as of now, you will in any case find out about how to change over your past code so it utilizes Tensorflow 2.0, and there are all-new and never-before-seen projects in this course, for example, time series determining and how to do stock expectations.
This course is intended for understudies who need to catch on quickly, yet there are moreover "top to bottom" segments on the off chance that you need to dig somewhat deeper into the hypothesis (like what is a misfortune capability, and what are the various kinds of slope drop draws near).
&nbsp;
High level Tensorflow subjects include:
Conveying a model with Tensorflow Serving (Tensorflow in the cloud)
Conveying a model with Tensorflow Lite (portable and inserted applications)
Disseminated Tensorflow preparation with Distribution Strategies
Composing your own custom Tensorflow model
Changing Tensorflow 1.x code over completely to Tensorflow 2.0
Constants, Factors, and Tensors
Energetic execution
Angle tape
&nbsp;
Teacher's Note: This course centers around expansiveness as opposed to profundity, with less hypothesis for building more cool stuff. In the event that you are searching for a more hypothesis thick course, this isn't it. For the most part, for every one of these subjects (recommender systems, natural language processing, reinforcement learning, computer vision, GANs, and so on) I as of now have courses uniquely centered around those points.
&nbsp;
Gratitude for perusing, and I'll see you in class!
&nbsp;
WHAT Request Would it be a good idea for me to TAKE YOUR COURSES Ready?:
Look at the talk "Machine Learning and computer based intelligence Essential Guide" (accessible in the FAQ of any of my courses, including the free Numpy course)
&nbsp;
Exceptional Highlights
Each line of code made sense of exhaustively - email me any time assuming that you clash
No sat around "composing" on the console like different courses - can we just be real for a moment, it's not possible for anyone to truly compose code worth learning about in only a little ways without any preparation
Not scared of college level math - get significant insights regarding calculations that different courses forget about
Who this course is for:
Amateurs to cutting edge understudies who need to find out about deep learning and man-made intelligence in Tensorflow 2.0
&nbsp;
<h2>Educators</h2>
Sluggish Developer Inc.
Artificial intelligence and machine learning engineer
<ul>
<li>4.6 Teacher Rating</li>
<li>149,846 Surveys</li>
<li>530,049 Understudies</li>
<li>34 Courses</li>
</ul>
Today, I invest the vast majority of my energy as an artificial intelligence and machine learning engineer with an emphasis on deep learning, despite the fact that I have likewise been known as an information researcher, huge information specialist, and full stack programmer.
I accepted my most memorable bosses degree quite a long time back in computer designing with a specialization in machine learning and example recognition. I accepted my second bosses degree in measurements with applications to monetary designing.
Experience incorporates internet promoting and computerized media as both an information researcher (streamlining snap and change rates) and large information engineer (building information processing pipelines). A few major information advances I oftentimes use are Hadoop, Pig, Hive, MapReduce, and Flash.
I've made deep learning models to anticipate active clicking factor and client conduct, as well with respect to image and flag processing and demonstrating text.
My work in suggestion systems has applied Reinforcement Learning and Cooperative Sifting, and we approved the outcomes utilizing A/B testing.
I have shown undergrad and graduate understudies in information science, measurements, machine learning, calculations, math, computer designs, and physical science for understudies going to colleges like Columbia College, NYU, Tracker School, and The New School.
Numerous organizations have profited from my web programming skill. I do all the backend (server), frontend (HTML/JS/CSS), and tasks/organization work. A portion of the innovations I've utilized are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Spine, and Rakish. For capacity/data sets I've utilized MySQL, Postgres, Redis, MongoDB, and the sky is the limit from there.
&nbsp;
<h2>4.7 course appraising 9K Reviews</h2>
Aiden T.
Rating: 5.0 out of 5a week prior
AT
&nbsp;
Magnificent course that covers such countless parts of deep learning through Tensorflow. In the end you have a full comprehension of many deep learning applications and the information to make your own undertakings or go after a position.
Yarin K.
Rating: 5.0 out of 52 weeks prior
&nbsp;
The course is extremely huge and the Sluggish Programer goes inside and out to a variety of subjects. The scratch pad he utilizes are excluded, be that as it may, the means he takes are simple and he explaines everything. Energetically suggest for individuals acquainted with the subject yet need to go inside and out and figure out a somewhat expansive range of DL?
&nbsp;
So Yiu N.
Rating: 4.5 out of 5a month prior
&nbsp;
Some arithmetic are very difficult to get, yet generally excellent web-based course to learn more on Machine Learning and Neural
&nbsp;
Mana M.
Rating: 5.0 out of 52 months prior
&nbsp;
Extraordinary course. Worth each penny and moment you spend. The educator is great in the two his insight and educating strategy.
<h2>Useful Links:</h2>
<ol>
<li>Official Tensorflow website: <a href="https://www.tensorflow.org/" target="_new">https://www.tensorflow.org/</a></li>
<li>Tensorflow documentation: <a href="https://www.tensorflow.org/api_docs" target="_new">https://www.tensorflow.org/api_docs</a></li>
<li>Tensorflow GitHub repository: <a href="https://github.com/tensorflow/tensorflow" target="_new">https://github.com/tensorflow/tensorflow</a></li>
<li>Tensorflow tutorials: <a href="https://www.tensorflow.org/tutorials" target="_new">https://www.tensorflow.org/tutorials</a></li>
<li>Tensorflow community forum: <a href="https://discuss.tensorflow.org/" target="_new">https://discuss.tensorflow.org/</a></li>
<li>Tensorflow Lite documentation: <a href="https://www.tensorflow.org/lite" target="_new">https://www.tensorflow.org/lite</a></li>
<li>Tensorflow Serving documentation: <a href="https://www.tensorflow.org/tfx/guide/serving" target="_new">https://www.tensorflow.org/tfx/guide/serving</a></li>
<li>Tensorflow Distribution Strategies documentation: <a href="https://www.tensorflow.org/guide/distributed_training" target="_new">https://www.tensorflow.org/guide/distributed_training</a></li>
<li>Tensorflow Models GitHub repository: <a href="https://github.com/tensorflow/models" target="_new">https://github.com/tensorflow/models</a></li>
<li>Tensorflow on YouTube: <a href="https://www.youtube.com/playlist?list=PLQY2H8rRoyvzoUYI26kHmKSJBedn3SQuB" target="_new">https://www.youtube.com/playlist?list=PLQY2H8rRoyvzoUYI26kHmKSJBedn3SQuB</a></li>
</ol>

Tensorflow 2.0: DL & AI 🔥

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Learn Microservices and Distributed Systems with this comprehensive course. Master microservices architecture, build distributed applications, and enhance your software development skills. Get certified and stay ahead in the tech industry
<h3>Building and Deploying Microservices from scratch</h3>
Stay Ahead of the Industry's Curve with Microservices Architecture
Learn the Most Advanced Approaches for Building Scalable, Reliable Systems
<h2>Hey Amigos 🙋🏽&zwj;♂️</h2>
Welcome to Microservices and Distributed Systems - one of the most in-demand courses on the platform and for a good reason, microservices are quickly becoming the dominant framework in the field and a critical skill for a professional Java developer.
The course will be a lot of hands-on, building a distributed application and learning the exact technology stack that makes a microservice tick. Join me today and master microservices with:​
&nbsp;
<ul>
<li>&bull;20-chapter roadmap made up of over 10 hours of video content:&nbsp;From fundamentals of the architecture to application deployment.</li>
<li>&bull;156 lessons:&nbsp;A step-by-step practical guide through every technology.</li>
<li>&bull;Microservices Application building:&nbsp;A comprehensive guide to give you all the knowledge needed to deploy components yourself.</li>
<li>&bull;Dedicated Discord Channel:&nbsp;Where you will be able to find answers to all your questions and chat with me and the students.</li>
</ul>
Who is this course for?
Simply put,&nbsp;anyone who is involved in software development, from developers, architects, testers and even ops professionals.
As microservices are becoming increasingly popular, more and more organizations look to adopt them in order to improve their software development processes. In turn learning, microservices can help you to improve your career prospects and earning potential.
So if you are willing to experiment with new technologies and are looking for courses trusted by thousands of professionals, keep scrolling to find out what they have to say.
&nbsp;
Why learn Microservices?
Learning microservices is essential for any programmer looking&nbsp;to remain competitive in the tech industry.&nbsp;Microservice architecture offers massive advantages over traditional monolithic architectures, such as greater scalability, the overall speed of development, and ease of updates.
The ability to break complex services into individual, independently deployable services and it also provides developers with more flexibility when building applications, allowing them to tailor their solutions according to the specific needs of the project owned by small teams.
In addition to having a positive impact on development cycles, microservices are becoming more popular in the IT industry as a cost-effective and efficient solution compared to traditional monolithic architecture.
By studying microservices, you can gain an edge in this emerging market and leverage your knowledge to create robust and reliable applications that match customer demands.
&nbsp;
Why would the Microservices course be right for you?
<ul>
<li>Gain&nbsp;experience&nbsp;building all of the common patterns in distributed systems such as configuration management, service discovery, circuit breakers, intelligent routing, micro-proxy, control bus, one-time tokens, global locks, leadership election, distributed sessions and cluster state</li>
<li>Taught by a teacher whose microservices tutorials have been viewed over 800,000 times&nbsp;on YouTube</li>
<li>Access to the&nbsp;55,000+ community&nbsp;of coders, many graduates of the microservices course</li>
<li>Getting help when you need it.&nbsp;Post a question on the dedicated discord channel or message me directly, you will get all the support you need to progress through the course</li>
</ul>
&nbsp;
Here is why you shouldn&rsquo;t waste your time and enroll now:
When trying to learn a complex concept like microservices,
It&rsquo;s easy to spend dozen of hours wasting time searching online instead of actually learning
Disjointed tutorials, confusing articles and a lack of support plague so many of the online resources that simply don&rsquo;t keep up with what you need.
With Amigoscode you will be learning from a trusted premium resource taught to you by a Java professional with years of microservices framework experience from his Software Engineer career at major companies in London.
The experience of students speaks for themselves and&nbsp;I hope soon you too will soon share your success story!
&nbsp;
Amigoscode Certificates
In addition to all the knowledge, skills and the application you have built, at the end of the course, you will be able to prove your efforts with a certificate issued by Amigoscode! Join thousands of others on Linkedin who proudly display their achievements:
&nbsp;

Microservices Amigoscode 🔥

Everything you need to build full-stack applications with Next.js 13+ (App Router) and TypeScript
&nbsp;
&nbsp;
Concise. Comprehensive.
Tired of piecing together disconnected tutorials or dealing with rambling, confusing instructors? This course is for you! It's perfectly structured into a series of bite-sized, easy-to-follow videos that cover both theory and practice.
&nbsp;
<h2>What You'll Learn</h2>
&nbsp;
<ul>
<li>Confidently build full-stack apps with Next.js 13+ and TypeScript</li>
</ul>
&nbsp;
<ul>
<li>Style Next.js applications with Tailwind or CSS modules</li>
</ul>
&nbsp;
<ul>
<li>Implement routing and navigation using the new App router</li>
</ul>
&nbsp;
<ul>
<li>Build RESTful APIs</li>
</ul>
&nbsp;
<ul>
<li>Use Prisma to integrate your Next.js apps with a database</li>
</ul>
&nbsp;
<ul>
<li>Handle file uploads</li>
</ul>
&nbsp;
<ul>
<li>Implement user authentication with NextAuth.js</li>
</ul>
&nbsp;
<ul>
<li>Send beautifully styled emails</li>
</ul>
&nbsp;
<ul>
<li>Optimize your apps for performance and SEO</li>
</ul>
&nbsp;
<ul>
<li>Deploy your Next.js apps</li>
</ul>
&nbsp;
<ul>
<li>Use VSCode shortcuts to increase your productivity</li>
</ul>
&nbsp;
<ul>
<li>Apply the latest techniques and best practices</li>
</ul>
&nbsp;
<ul>
<li>Troubleshoot errors with ease</li>
</ul>
&nbsp;
<h2>Course Content</h2>
5 Hours . 12 Sections . 110 Lessons
<h3>Getting Started(5m)</h3>
<ul>
<li>Introduction<a class="editor-rtfLink" href="https://codewithmosh.teachable.com/courses/mastering-next-js-13-with-typescript/lectures/49189423" target="_blank" rel="noopener">PREVIEW</a></li>
<li>Prerequisites<a class="editor-rtfLink" href="https://codewithmosh.teachable.com/courses/mastering-next-js-13-with-typescript/lectures/49120014" target="_blank" rel="noopener">PREVIEW</a></li>
<li>Course Overview<a class="editor-rtfLink" href="https://codewithmosh.teachable.com/courses/mastering-next-js-13-with-typescript/lectures/49120012" target="_blank" rel="noopener">PREVIEW</a></li>
<li>Source Code</li>
<li>Questions and Support</li>
<li>Connect with Me</li>
<li>Learning Paths</li>
</ul>
<h3>Next.js Fundamentals(36m)</h3>
<h3>Styling(22m)</h3>
<h3>Routing and Navigation(49m)</h3>
<h3>Building APIs(27m)</h3>
<h3>Database Integration with Prisma(36m)</h3>
<h3>Uploading Files(14m)</h3>
<h3>Authentication with Next Auth(56m)</h3>
<h3>Sending Emails(15m)</h3>
<h3>Optimizations(37m)</h3>
<h3>Deployment(17m)</h3>
<h3>Conclusion(25s)</h3>
&nbsp;
Target student
<h2>Who Is This For?</h2>
<ul>
<li>&nbsp;</li>
<li>Web developers seeking to master Next.js 13+ and TypeScript for full-stack app development</li>
<li>&nbsp;</li>
<li>Frontend devs looking to explore full-stack development with Next.js.</li>
<li>&nbsp;</li>
<li>Next.js developers looking to fill in knowledge gaps and solidify their expertise</li>
</ul>
&nbsp;
What you should know
<h2>Prerequisites</h2>
You don't need prior knowledge of Next.js to take this course. However, you should have some basic knowledge of React and TypeScript.
Here are the courses we recommend if you need to strengthen the fundamentals.
<ul style="list-style-type: circle;">
<li class="transition duration-700 text-center sm:mb-4 cursor-pointer hover:text-pink-600 text-base sm:text-xl font-semibold"><a href="https://www.cheapuniverse.org/post/react-18-from-zero-to-hero-code-with-mosh">React 18: From Zero to Hero ( Code With Mosh )</a></li>
<li class="transition duration-700 text-center sm:mb-4 cursor-pointer hover:text-pink-600 text-base sm:text-xl font-semibold"><a href="https://www.cheapuniverse.org/post/react-intermediate-topics-code-with-mosh">React: Intermediate Topics (Code With Mosh)</a></li>
</ul>

Mastering Next.js 13 🔥

Mastering Next.js 13 with TypeScript [Code With Mosh]

Mastering Next.js 13 with TypeScript [Code With Mosh]

What You'll Learn

Course Content

Getting Started(5m)

Next.js Fundamentals(36m)

Styling(22m)

Routing and Navigation(49m)

Building APIs(27m)

Database Integration with Prisma(36m)

Uploading Files(14m)

Authentication with Next Auth(56m)

Sending Emails(15m)

Optimizations(37m)

Deployment(17m)

Conclusion(25s)

Who Is This For?

Prerequisites

Harry Potter

Leave a comment

0 Comment

Membership Plans

How to download ??

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Get $200 credit Instantly

Offer available for limited time
( Take advantage of free credits 👇 )

Related Posts

Tags

Mastering Next.js 13 with TypeScript [Code With Mosh]

What You'll Learn

Course Content

Getting Started(5m)

Next.js Fundamentals(36m)

Styling(22m)

Routing and Navigation(49m)

Building APIs(27m)

Database Integration with Prisma(36m)

Uploading Files(14m)

Authentication with Next Auth(56m)

Sending Emails(15m)

Optimizations(37m)

Deployment(17m)

Conclusion(25s)

Who Is This For?

Prerequisites

Harry Potter

Leave a comment

0 Comment

Membership Plans

How to download ??

This site is hosted on Digital Ocean

Get $200 credit Instantly

Offer available for limited time ( Take advantage of free credits 👇 )

Related Posts

Tags

Offer available for limited time
( Take advantage of free credits 👇 )