Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert – Telegram
Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert
74.4K subscribers
6 photos
293 links
We provide unlimited Free Courses with Certificate to learn Python, Data Science, Java, Web development, AI, ML, Finance, Hacking, Marketing and many more from top websites.

For promotions: @love_data
Download Telegram
Channels that you MUST follow in 2023:

@getjobss - Jobs and Internship Opportunities

@englishlearnerspro - improve your English

@datasciencefun - Learn Data Science and Machibe Learning

@crackingthecodinginterview - boost your coding knowledge

@learndataanalysis - Data Analysis Books

@programming_guide - Coding Books
👍2
🔟 Web development project ideas for beginners

Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.

To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.

Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.

E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.

Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.

Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.

Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.

Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.

Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.

Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.

Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.

Free Resources to learn web development https://news.1rj.ru/str/free4unow_backup/554

ENJOY LEARNING 👍👍
3👍1
🔟 Data Science Project Ideas for Freshers

Exploratory Data Analysis (EDA) on a Dataset: Choose a dataset of interest and perform thorough EDA to extract insights, visualize trends, and identify patterns.

Predictive Modeling: Build a simple predictive model, such as linear regression, to predict a target variable based on input features. Use libraries like scikit-learn to implement the model.

Classification Problem: Work on a classification task using algorithms like decision trees, random forests, or support vector machines. It could involve classifying emails as spam or not spam, or predicting customer churn.

Time Series Analysis: Analyze time-dependent data, like stock prices or temperature readings, to forecast future values using techniques like ARIMA or LSTM.

Image Classification: Use convolutional neural networks (CNNs) to build an image classification model, perhaps classifying different types of objects or animals.

Natural Language Processing (NLP): Create a sentiment analysis model that classifies text as positive, negative, or neutral, or build a text generator using recurrent neural networks (RNNs).

Clustering Analysis: Apply clustering algorithms like k-means to group similar data points together, such as segmenting customers based on purchasing behaviour.

Recommendation System: Develop a recommendation engine using collaborative filtering techniques to suggest products or content to users.

Anomaly Detection: Build a model to detect anomalies in data, which could be useful for fraud detection or identifying defects in manufacturing processes.

A/B Testing: Design and analyze an A/B test to compare the effectiveness of two different versions of a web page or app feature.

Remember to document your process, explain your methodology, and showcase your projects on platforms like GitHub or a personal portfolio website.

Free datasets to build the projects
👇👇
https://news.1rj.ru/str/datasciencefun/1126

ENJOY LEARNING 👍👍
👍5
🔟 Project Ideas for a data analyst

Customer Segmentation: Analyze customer data to segment them based on their behaviors, preferences, or demographics, helping businesses tailor their marketing strategies.

Churn Prediction: Build a model to predict customer churn, identifying factors that contribute to churn and proposing strategies to retain customers.

Sales Forecasting: Use historical sales data to create a predictive model that forecasts future sales, aiding inventory management and resource planning.

Market Basket Analysis: Analyze
transaction data to identify associations between products often purchased together, assisting retailers in optimizing product placement and cross-selling.

Sentiment Analysis: Analyze social media or customer reviews to gauge public sentiment about a product or service, providing valuable insights for brand reputation management.

Healthcare Analytics: Examine medical records to identify trends, patterns, or correlations in patient data, aiding in disease prediction, treatment optimization, and resource allocation.

Financial Fraud Detection: Develop algorithms to detect anomalous transactions and patterns in financial data, helping prevent fraud and secure transactions.

A/B Testing Analysis: Evaluate the results of A/B tests to determine the effectiveness of different strategies or changes on websites, apps, or marketing campaigns.

Energy Consumption Analysis: Analyze energy usage data to identify patterns and inefficiencies, suggesting strategies for optimizing energy consumption in buildings or industries.

Real Estate Market Analysis: Study housing market data to identify trends in property prices, rental rates, and demand, assisting buyers, sellers, and investors in making informed decisions.

Remember to choose a project that aligns with your interests and the domain you're passionate about.

Data Analyst Roadmap
👇👇
https://news.1rj.ru/str/sqlspecialist/379

ENJOY LEARNING 👍👍
👍4
🔟 steps to help you start Freelancing

Choose Your Niche: Decide on the specific field or industry you want to freelance in. This could be web development, graphic design, writing, digital marketing, data science, or any other skill you possess. Ensure you have the necessary skills and knowledge for your chosen niche.

Quick Resources to grab these skills:

https://news.1rj.ru/str/webdevcoursefree/429

https://news.1rj.ru/str/datasciencefree/264

Create a Portfolio: Even if you're just starting, you can create a portfolio of personal projects or work you've done for friends and family. This will help showcase your abilities to clients.

Few Project ideas to start with:

https://news.1rj.ru/str/datasciencefun/1294

https://news.1rj.ru/str/Programming_experts/385

https://news.1rj.ru/str/pythonspecialist/33

Clear Goals
: Define your freelancing goals, such as the type of clients you want to work with, your income targets, and your desired work-life balance.

Create an Online Presence: Build a professional online presence through a personal website or profiles on freelancing platforms like Upwork, Freelancer, Fiverr, or specialized websites related to your niche.

Market Yourself: Use social media, networking events, and online communities to connect with potential clients and other freelancers. Share your expertise and engage in discussions related to your field.

Set Pricing and Contracts: Determine your pricing structure and create clear contracts for your projects. Make sure you understand how to negotiate and set expectations with clients.

Start Small: In the beginning, take on smaller projects to build your reputation and gain experience. As you accumulate positive reviews and referrals, you can gradually aim for larger and higher-paying gigs

Deliver Quality Work: Always prioritize delivering high-quality work on time. Happy clients are more likely to hire you again or refer you to others.

Seek Feedback: After completing projects, ask clients for feedback. Constructive feedback can help you improve your skills and services.

Adapt and Learn: The freelance landscape can change, so be prepared to adapt to new technologies and trends. Continuously update your skills and knowledge.

Remember that freelancing often requires patience and persistence. Building a steady client base and income may take time, but with dedication and a commitment to delivering quality work, you can establish a successful freelance career.

ENJOY LEARNING 👍👍
👍4
FREE RESOURCES TO LEARN

🔰 SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

https://news.1rj.ru/str/sqlanalyst/38

🔰 Python
http://cs50.harvard.edu/python/2022/

https://news.1rj.ru/str/pythondevelopersindia/4

🔰Statistics and R
https://edx.org/learn/r-programming/harvard-university-statistics-and-r

🔰Data Science: R Basics
https://edx.org/learn/r-programming/harvard-university-data-science-r-basics

🔰 Excel and PowerBI
http://learn.microsoft.com/en-gb/training/paths/modern-analytics/

https://news.1rj.ru/str/excel_analyst

🔰Data Science: Visualization
https://edx.org/learn/data-visualization/harvard-university-data-science-visualization

🔰Data Science: Machine Learning
https://edx.org/learn/machine-learning/harvard-university-data-science-machine-learning

🔰 R
http://cognitiveclass.ai/courses/r-101

🔰 Tableau
http://tableau.com/learn/training

🔰 PowerBI
http://learn.microsoft.com/en-us/users/collinschedler-0717/collections/m14nt4rdwnwp04

https://news.1rj.ru/str/PowerBI_analyst

🔰Data Science: Productivity Tools
https://edx.org/learn/data-science/harvard-university-data-science-productivity-tools

🔰Data Science: Probability
https://edx.org/learn/probability/harvard-university-data-science-probability

🔰 Mathematics
http://ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

🔰 Statistics
http://cognitiveclass.ai/courses/statistics-101

🔰 Data Visualization
http://pll.harvard.edu/course/data-science-visualization

🔰 Machine Learning
http://developers.google.com/machine-learning/crash-course

🔰 Deep Learning
http://introtodeeplearning.com

https://news.1rj.ru/str/machinelearning_deeplearning

🔰Data Science: Linear Regression
https://pll.harvard.edu/course/data-science-linear-regression/2023-10

🔰Data Science: Wrangling
https://edx.org/learn/data-science/harvard-university-data-science-wrangling

🔰 Linear Algebra
http://pll.harvard.edu/course/data-analysis-life-sciences-2-introduction-linear-models-and-matrix-algebra

🔰 Probability
http://pll.harvard.edu/course/data-science-probability

🔰Introduction to Linear Models and Matrix Algebra
https://edx.org/learn/linear-algebra/harvard-university-introduction-to-linear-models-and-matrix-algebra

🔰Data Science: Capstone
https://edx.org/learn/data-science/harvard-university-data-science-capstone

https://news.1rj.ru/str/pythonspecialist/55

🔰 Data Analysis
http://pll.harvard.edu/course/data-analysis-life-sciences-4-high-dimensional-data-analysis

https://news.1rj.ru/str/learndataanalysis

Get a remote job using these AI tools

https://news.1rj.ru/str/crackingthecodinginterview/718

ENJOY LEARNING 👍👍
👍42👏1
Steps to become a full-stack developer

Learn the Fundamentals: Start with the basics of programming languages, web development, and databases. Familiarize yourself with technologies like HTML, CSS, JavaScript, and SQL.

Front-End Development: Master front-end technologies like HTML, CSS, and JavaScript. Learn about frameworks like React, Angular, or Vue.js for building user interfaces.

Back-End Development: Gain expertise in a back-end programming language like Python, Java, Ruby, or Node.js. Learn how to work with servers, databases, and server-side frameworks like Express.js or Django.

Databases: Understand different types of databases, both SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB). Learn how to design and query databases effectively.

Version Control: Learn Git, a version control system, to track and manage code changes collaboratively.

APIs and Web Services: Understand how to create and consume APIs and web services, as they are essential for full-stack development.

Development Tools: Familiarize yourself with development tools, including text editors or IDEs, debugging tools, and build automation tools.

Server Management: Learn how to deploy and manage web applications on web servers or cloud platforms like AWS, Azure, or Heroku.

Security: Gain knowledge of web security principles to protect your applications from common vulnerabilities.

Build a Portfolio: Create a portfolio showcasing your projects and skills. It's a powerful way to demonstrate your abilities to potential employers.

Project Experience: Work on real projects to apply your skills. Building personal projects or contributing to open-source projects can be valuable.

Continuous Learning: Stay updated with the latest web development trends and technologies. The tech industry evolves rapidly, so continuous learning is crucial.

Soft Skills: Develop good communication, problem-solving, and teamwork skills, as they are essential for working in development teams.

Job Search: Start looking for full-stack developer job opportunities. Tailor your resume and cover letter to highlight your skills and experience.

Interview Preparation: Prepare for technical interviews, which may include coding challenges, algorithm questions, and discussions about your projects.

Continuous Improvement: Even after landing a job, keep learning and improving your skills. The tech industry is always changing.

Full Stack Web Development Bootcamp

https://news.1rj.ru/str/webdevcoursefree/461

Remember that becoming a full-stack developer takes time and dedication. It's a journey of continuous learning and improvement, so stay persistent and keep building your skills.

ENJOY LEARNING 👍👍
👍41
Here is a list of Important interview questions

SQL INTERVIEW QUESTIONS WITH IMPORTANT TOPICS
👇👇
https://news.1rj.ru/str/sqlspecialist/426

Data Analyst Interview Questions
👇👇
https://news.1rj.ru/str/DataAnalystInterview/69

Python Interview Questions and Answers
👇👇
https://news.1rj.ru/str/dsabooks/96

Data Science Interview Questions
👇👇
https://news.1rj.ru/str/datasciencefun/1058

Advanced Power BI Interview Questions
👇👇
https://news.1rj.ru/str/sqlspecialist/422

DSA INTERVIEW QUESTIONS
👇👇
https://news.1rj.ru/str/crackingthecodinginterview/77

Use Chat GPT to prepare for your next INTERVIEW
👇👇
https://news.1rj.ru/str/getjobss/1483

ENJOY LEARNING 👍👍
👍4
Steps to become a data analyst

Learn the Basics of Data Analysis:
Familiarize yourself with foundational concepts in data analysis, statistics, and data visualization. Online courses and textbooks can help.
Free books & other useful data analysis resources - https://news.1rj.ru/str/learndataanalysis

Develop Technical Skills:
Gain proficiency in essential tools and technologies such as:

SQL: Learn how to query and manipulate data in relational databases.
Free Resources- @sqlanalyst

Excel: Master data manipulation, basic analysis, and visualization.
Free Resources- @excel_analyst

Data Visualization Tools: Become skilled in tools like Tableau, Power BI, or Python libraries like Matplotlib and Seaborn.
Free Resources- @PowerBI_analyst

Programming: Learn a programming language like Python or R for data analysis and manipulation.
Free Resources- @pythonanalyst

Statistical Packages: Familiarize yourself with packages like Pandas, NumPy, and SciPy (for Python) or ggplot2 (for R).

Hands-On Practice:
Apply your knowledge to real datasets. You can find publicly available datasets on platforms like Kaggle or create your datasets for analysis.

Build a Portfolio:
Create data analysis projects to showcase your skills. Share them on platforms like GitHub, where potential employers can see your work.

Networking:
Attend data-related meetups, conferences, and online communities. Networking can lead to job opportunities and valuable insights.

Data Analysis Projects:
Work on personal or freelance data analysis projects to gain experience and demonstrate your abilities.

Job Search:
Start applying for entry-level data analyst positions or internships. Look for job listings on company websites, job boards, and LinkedIn.
Jobs & Internship opportunities: @getjobss

Prepare for Interviews:
Practice common data analyst interview questions and be ready to discuss your past projects and experiences.

Continual Learning:
The field of data analysis is constantly evolving. Stay updated with new tools, techniques, and industry trends.

Soft Skills:
Develop soft skills like critical thinking, problem-solving, communication, and attention to detail, as they are crucial for data analysts.

Never ever give up:
The journey to becoming a data analyst can be challenging, with complex concepts and technical skills to learn. There may be moments of frustration and self-doubt, but remember that these are normal parts of the learning process. Keep pushing through setbacks, keep learning, and stay committed to your goal.

ENJOY LEARNING 👍👍
👍1
FREE RESOURCES to Learn Data Visualization
👇👇

Data Visualization in Tableau Free Udacity Course

https://imp.i115008.net/2rMPVg

Tableau Tutorial for Beginners FREE UDEMY COURSE

https://bit.ly/3H3uhX5

Free Power BI course from Microsoft

https://docs.microsoft.com/en-us/users/microsoftpowerplatform-5978/collections/k8xidwwnzk1em

Data Visualization with Python FREE COURSE

https://cognitiveclass.ai/courses/data-visualization-with-python

Free Training Videos for Tableau

https://www.tableau.com/learn/training/20201

Learn Power BI Basics for Free from Udemy

https://bit.ly/3sTa6Gj

Microsoft Excel - Basic Data Visualization in Excel
[4.4 star ratings out of 5]

https://bit.ly/3JDEs6A

Handbook of Data Visualization FREE BOOK

https://haralick.org/DV/Handbook_of_Data_Visualization.pdf

Tableau tutorial

https://news.1rj.ru/str/PowerBI_analyst/19

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍
👍41
Stepwise Guide on becoming a software engineer 😄👇

Choose a Programming Language: Start by picking a programming language to learn. Popular choices for beginners include Python, JavaScript, or Java.

Learn the Basics: Begin with the fundamentals of programming, including variables, data types, control structures (if-else, loops), and basic algorithms.

Data Structures and Algorithms: Gain a solid understanding of data structures (arrays, linked lists, stacks, queues) and algorithms. Telegram channels like @crackingthecodinginterview can be helpful.

Online Courses and Tutorials: Take advantage of online courses and tutorials. Platforms like Coursera, edX, and Codecademy offer a wide range of programming courses. Many free resources are shared in this channel. Just search for the desired skill/course based on your interest in this channel.

Build Projects: Practical experience is key. Create small software projects to apply what you've learned. Start with simple projects and gradually work your way up to more complex ones.

Version Control (Git): Learn how to use Git for version control. It's essential for collaborative software development.

Explore Different Fields: Software development is vast. Explore different areas like web development, mobile app development, data science, or game development to find your niche.

Contribute to Open Source: Consider contributing to open-source projects. It's a great way to gain real-world experience, collaborate with others, and build a portfolio.

Build a Portfolio: Create a portfolio of your projects on platforms like GitHub or a personal website. Showcase your skills and projects to potential employers.

Internships and Job Search: Look for internships or entry-level positions to gain professional experience. Tailor your resume and cover letter to highlight your skills and projects. Many telegram channels like @getjobss or linkedin platform might be useful to find your desired job/internship.

Interview Preparation: Practice coding interviews. Use resources like LeetCode, HackerRank, or InterviewBit to improve your problem-solving skills.

Soft Skills: Develop soft skills like communication, teamwork, and time management. These are essential in a professional environment.

Continuous Learning: Technology evolves rapidly. Stay updated by reading blogs, books, and taking advanced courses to deepen your knowledge.

Build a Strong Online Presence: Engage in tech communities, write blog posts, or share your insights on platforms like LinkedIn to showcase your expertise.

Be Persistent: Landing your first job can be challenging. Keep applying, learning, and improving your skills. Don't get discouraged by rejections.
Remember that becoming a software engineer is a journey, and it may take time. Stay committed to learning and adapting to new technologies, and you'll progress in your career.

ENJOY LEARNING 👍👍
👍4
Free Online courses with certificate from Microsoft

Python for beginners
https://learn.microsoft.com/en-us/training/paths/beginner-python/

Get started with Azure Cosmos DB for NoSQL
https://learn.microsoft.com/en-us/training/paths/get-started-azure-cosmos-db-sql-api/

Introduction to machine learning with Python and Azure Notebooks
https://learn.microsoft.com/en-us/training/paths/intro-to-ml-with-python/

Automate development tasks by using GitHub Actions
https://bit.ly/48E75xT

SQL, Power BI & AI Fundamentals
https://bit.ly/3ZL2820

Write your first code using C#
https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/

Join @free4unow_backup for more free resources

ENJOY LEARNING 👍👍
👍42