Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

⚡️The best job today is to be a trader This year, they earned an average of $20,000 a month, working from home, traveling or in a country house. And the smartest ones are making hundreds of thousands. Do you want the same? You don't need to be a genius to make money from deals, just start reading Evelyn's channel. She explains in detail how to make $4,000 in the first week just by copying her trades, without any risks or long training. ✅Subscribe — everything you need to get started is there: @trading_evelyn

𝗛𝗼𝘄 𝘁𝗼 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱😍 Want to break into Financial Data Analytics but don’t know where to start? Here’s your ultimate step-by-step roadmap to landing a job in this high-demand field. 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/42aGUwb 🎯 🚀 Ready to Start?

Must-have tools for beginners: ⤷ Excel (for basics) ⤷ SQL (for querying) ⤷ Tableau/Power BI (for viz) ⤷ ChatGPT (for practice help, not copy-paste) ⤷ Kaggle (for datasets & real-world exposure) Start with these. No need for 10 certifications.

Useful tips

Data Projects

𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 Upgrade Your Tech Skills in 2025—For FREE! 🔹 Introduction to Cybersecurity 🔹 Networking Essentials 🔹 Introduction to Modern AI 🔹 Discovering Entrepreneurship 🔹 Python for Beginners 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4chn8Us Enroll For FREE & Get Certified 🎓

9-Month Roadmap to Become a Data Analyst: Month 1-2: Excel + SQL Month 3: Data Cleaning + EDA Month 4-5: Tableau / Power BI Month 6: Real Projects + Case Studies Month 7: Stats + Business Metrics Month 8: Resume + Portfolio Month 9: Apply. Interview. Repeat. No shortcut.

Hey guys, Here are some best Telegram Channels for free education in 2024 👇👇 Free Courses with Certificate Web Development Free Resources Data Science & Machine Learning Programming Free Books Python Free Courses Ethical Hacking & Cyber Security English Speaking & Communication Stock Marketing & Investment Banking Coding Projects Jobs & Internship Opportunities Crack your coding Interviews Udemy Free Courses with Certificate Free access to all the Paid Channels 👇👇 https://t.me/addlist/4q2PYC0pH_VjZDk5 Do react with ♥️ if you need more content like this ENJOY LEARNING 👍👍

𝟰 𝗙𝗥𝗘𝗘 𝗦𝗤𝗟 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 - Introduction to SQL (Simplilearn)  - Intro to SQL (Kaggle)  - Introduction to Database & SQL Querying  - SQL for Beginners – Microsoft SQL Server  Start Learning Today – 4 Free SQL Courses 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/42nUsWr Enroll For FREE & Get Certified 🎓

Use Python to turn messy data into valuable insights! Here are the main functions you need to know: 1. 𝗱𝗿𝗼𝗽𝗻𝗮(): Clean up your dataset by removing missing values. Use df.dropna() to eliminate rows or columns with NaNs and keep your data clean.     2. 𝗳𝗶𝗹𝗹𝗻𝗮(): Replace missing values with a specified value or method. With the help of df.fillna(value) you maintain data integrity without losing valuable information.     3. 𝗱𝗿𝗼𝗽_𝗱𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗲𝘀(): Ensure your data is unique and accurate. Use df.drop_duplicates() to remove duplicate rows and avoid skewing your analysis by aggregating redundant data.     4. 𝗿𝗲𝗽𝗹𝗮𝗰𝗲(): Substitute specific values throughout your dataset. The function df.replace(to_replace, value) allows for efficient correction of errors and standardization of data.     5. 𝗮𝘀𝘁𝘆𝗽𝗲(): Convert data types for consistency and accuracy. Use the cast function df['column'].astype(dtype) to ensure your data columns are in the correct format you need for your analysis.     6. 𝗮𝗽𝗽𝗹𝘆(): Apply custom functions to your data. df['column'].apply(func) lets you perform complex transformations and calculations. It works with both standard and lambda functions.     7. 𝘀𝘁𝗿.𝘀𝘁𝗿𝗶𝗽(): Clean up text data by removing leading and trailing whitespace. Using df['column'].str.strip() helps you to avoid hard-to-spot errors in string comparisons.     8. 𝘃𝗮𝗹𝘂𝗲_𝗰𝗼𝘂𝗻𝘁𝘀(): Get a quick summary of the frequency of values in a column. df['column'].value_counts() helps you understand the distribution of your data.     9. 𝗽𝗱.𝘁𝗼_𝗱𝗮𝘁𝗲𝘁𝗶𝗺𝗲(): Convert strings to datetime objects for accurate date and time manipulation. For time series analysis the use of pd.to_datetime(df['column']) will often be one of your first steps in data preparation.     10. 𝗴𝗿𝗼𝘂𝗽𝗯𝘆(): Aggregates data based on specific columns. Use df.groupby('column') to perform operations like sum, mean, or count on grouped data. Learn to use these Python functions, to be able to transform a pile of messy data into the starting point of an impactful analysis.

🎓 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗿𝗼𝗺 𝗢𝗽𝗲𝗻 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 – 𝗟𝗲𝗮𝗿𝗻, 𝗚𝗿𝗼𝘄 & 𝗨𝗽𝘀𝗸𝗶𝗹𝗹!😍 If you’re just starting your learning journey or looking to level up your skills—this is your golden opportunity! 🌟 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4cuo73X ⏳ Don’t miss out—bookmark this for later!

Just start Start with SQL Start with Excel Start with PowerBi Just start

Want to make a transition to a career in data? Here is a 7-step plan for each data role Data Scientist Statistics and Math: Advanced statistics, linear algebra, calculus. Machine Learning: Supervised and unsupervised learning algorithms. xData Wrangling: Cleaning and transforming datasets. Big Data: Hadoop, Spark, SQL/NoSQL databases. Data Visualization: Matplotlib, Seaborn, D3.js. Domain Knowledge: Industry-specific data science applications. Data Analyst Data Visualization: Tableau, Power BI, Excel for visualizations. SQL: Querying and managing databases. Statistics: Basic statistical analysis and probability. Excel: Data manipulation and analysis. Python/R: Programming for data analysis. Data Cleaning: Techniques for data preprocessing. Business Acumen: Understanding business context for insights. Data Engineer SQL/NoSQL Databases: MySQL, PostgreSQL, MongoDB, Cassandra. ETL Tools: Apache NiFi, Talend, Informatica. Big Data: Hadoop, Spark, Kafka. Programming: Python, Java, Scala. Data Warehousing: Redshift, BigQuery, Snowflake. Cloud Platforms: AWS, GCP, Azure. Data Modeling: Designing and implementing data models. #data

𝟱 𝗙𝗿𝗲𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗹𝗮𝗻𝘀 𝘁𝗼 𝗨𝗽𝘀𝗸𝗶𝗹𝗹 𝗶𝗻 𝗧𝗲𝗰𝗵 & 𝗔𝗜!😍 Looking to boost your tech career?🚀 These free learning plans will help you stay ahead in DevOps, AI, Cloud Security, Data Analytics, and Machine Learning!📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4ijtDI2 Perfect for Beginners & Professionals Looking to Upskill!✅️

Learn Data Science from The Best Data Scientist In Top Tech Companies! Become a Successful Data Scientist In Top MNCs🔥 Eligibility:- BTech / BCA / BSc 🌟 2000+ Students Placed 🤝 500+ Hiring Partners 💼 Avg. Rs. 7.4 LPA 🚀 41 LPA Highest Package 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰👇 :- https://tracking.acciojob.com/g/PUfdDxgHR Hurry, limited seats available!

If you want a data role THIS year, don't just create value, CAPTURE it. 🟠 Creating value - Build end-to-end data projects - Work with cloud providers (AWS, Azure, GCP) - Learn fundamentals (SQL, Excel, Power BI, Python) 🟢 Capture value - Show your projects online (GitHub, LinkedIn) - Network with data pros and hiring managers - Quantify your achievements on your resume + interviews

𝟱 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 Whether you’re a complete beginner or looking to level up, these courses cover Excel, Power BI, Data Science, and Real-World Analytics Projects to make you job-ready. 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3DPkrga All The Best 🎊

Use data creatively, but responsibly 😉