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55 AI Tools to Start Your Online Business in 2023: 👇👇 https://t.me/ai_best_tools/54

2023 Complete SQL Bootcamp from Zero to Hero in SQL 👇👇 https://t.me/udemy_free_courses_with_certi/2418

Google is hiring for Data Analytics Apprenticeship Program 👇👇 https://www.linkedin.com/posts/sql-analysts_google-dataanalytics-dataanalysts-activity-7141298566135795712-sDfW?utm_source=share&utm_medium=member_android

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Five-Day Online Hands-on Training Program on Analysis Qualitative Data using NVivo Software 🗓December 18 – 22, 2023 ⏰6:30pm – 8:00pm IST 📑 Registration Fee: Rs.600/- & /- & Foreigners: 15 USD (Payment link: PayPal.Me/LekSha22) [Team / Group Registrations: Every 4th registration is free (i.e., no fee for the 4th registration).] ✅ Registration Link: https://forms.gle/QpcTXzjt5at7f1JG8 🌟 Takeaways: 1. PPT, Data sets, eBooks included. 2. Recorded videos available after workshop for 60 days 3. 5 Days Live Lectures 4. e-Certificate 5. Free trial version of NVivo Software 6. Opportunity to use your data sets to clarify your doubts. 7. Boosted skills in qualitative data analysis and interpretation of results 📌 For more updates, WhatsApp Group: https://chat.whatsapp.com/JiM8SsVw4er4f4sq21TWKk

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Master MySQL in 30 Days 👇👇 https://www.linkedin.com/posts/sql-analysts_sql-dataanalytics-activity-7140203618682519552-V1fW?utm_source=share&utm_medium=member_android

Complete Syllabus for Data Analytics interview: SQL: 1. Basic    - SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING    - Basic JOINS (INNER, LEFT, RIGHT, FULL)    - Creating and using simple databases and tables 2. Intermediate    - Aggregate functions (COUNT, SUM, AVG, MAX, MIN)    - Subqueries and nested queries - Common Table Expressions (WITH clause)    - CASE statements for conditional logic in queries 3. Advanced    - Advanced JOIN techniques (self-join, non-equi join)    - Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag)    - optimization with indexing    - Data manipulation (INSERT, UPDATE, DELETE) Python: 1. Basic    - Syntax, variables, data types (integers, floats, strings, booleans)    - Control structures (if-else, for and while loops)    - Basic data structures (lists, dictionaries, sets, tuples)    - Functions, lambda functions, error handling (try-except)    - Modules and packages 2. Pandas & Numpy    - Creating and manipulating DataFrames and Series    - Indexing, selecting, and filtering data    - Handling missing data (fillna, dropna)    - Data aggregation with groupby, summarizing data    - Merging, joining, and concatenating datasets 3. Basic Visualization    - Basic plotting with Matplotlib (line plots, bar plots, histograms)    - Visualization with Seaborn (scatter plots, box plots, pair plots)    - Customizing plots (sizes, labels, legends, color palettes)    - Introduction to interactive visualizations (e.g., Plotly) Excel: 1. Basic    - Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.)    - Introduction to charts and basic data visualization    - Data sorting and filtering    - Conditional formatting 2. Intermediate    - Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF)    - PivotTables and PivotCharts for summarizing data    - Data validation tools    - What-if analysis tools (Data Tables, Goal Seek) 3. Advanced    - Array formulas and advanced functions    - Data Model & Power Pivot - Advanced Filter - Slicers and Timelines in Pivot Tables    - Dynamic charts and interactive dashboards Power BI: 1. Data Modeling    - Importing data from various sources    - Creating and managing relationships between different datasets    - Data modeling basics (star schema, snowflake schema) 2. Data Transformation    - Using Power Query for data cleaning and transformation    - Advanced data shaping techniques    - Calculated columns and measures using DAX 3. Data Visualization and Reporting   - Creating interactive reports and dashboards    - Visualizations (bar, line, pie charts, maps)    - Publishing and sharing reports, scheduling data refreshes Statistics Fundamentals: Mean, Median, Mode, Standard Deviation, Variance, Probability Distributions, Hypothesis Testing, P-values, Confidence Intervals, Correlation, Simple Linear Regression, Normal Distribution, Binomial Distribution, Poisson Distribution. ENJOY LEARNING 👍👍

Steps to become data analyst when you are fresher 👇👇 1 - First try to focus 3 mandatory skills i.e. Sql, Ms excel and python - - For sql you can refer Ankit Bansal Or Thoufiq Mohammed (techtfq) on @sqlanalyst - For Ms excel refer Leila Gharani or @excel_analyst - For python refer freecodecamp from YouTube or @pythonanalyst 2 - After that try to be clear with basic idea of tableau or powerbi. (Not mandatory for every job). You can refer this channel for free resources https://t.me/PowerBI_analyst 3 - Add your college project in your resume, if it's a data science related project it will help a lot. If you don't have project then you can make some dashboarding projects from YouTube in tableau/powerbi. 4 - And start applying for jobs which is having 0-1 yr experience required, you can also apply for 1 yr experience required job in analytics because sometimes they may consider fresher also. You can refer this channel @jobs_sql for job opportunities