𝟯 𝗙𝗿𝗲𝗲 𝗧𝗖𝗦 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗘𝘃𝗲𝗿𝘆 𝗙𝗿𝗲𝘀𝗵𝗲𝗿 𝗠𝘂𝘀𝘁 𝗧𝗮𝗸𝗲 𝘁𝗼 𝗚𝗲𝘁 𝗝𝗼𝗯-𝗥𝗲𝗮𝗱𝘆😍
🎯 If You’re a Fresher, These TCS Courses Are a Must-Do📄✔️
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🎯 If You’re a Fresher, These TCS Courses Are a Must-Do📄✔️
Stepping into the job market can be overwhelming—but what if you had certified, expert-backed training that actually prepares you?👨🎓✨️
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Master SQL step-by-step! From basics to advanced, here are the key topics you need for a solid SQL foundation. 🚀
1. Foundations:
- Learn basic SQL syntax, including SELECT, FROM, WHERE clauses.
- Understand data types, constraints, and the basic structure of a database.
2. Database Design:
- Study database normalization to ensure efficient data organization.
- Learn about primary keys, foreign keys, and relationships between tables.
3. Queries and Joins:
- Practice writing simple to complex SELECT queries.
- Master different types of joins (INNER, LEFT, RIGHT, FULL) to combine data from multiple tables.
4. Aggregation and Grouping:
- Explore aggregate functions like COUNT, SUM, AVG, MAX, and MIN.
- Understand GROUP BY clause for summarizing data based on specific criteria.
5. Subqueries and Nested Queries:
- Learn how to use subqueries to perform operations within another query.
- Understand the concept of nested queries and their practical applications.
6. Indexing and Optimization:
- Study indexing for enhancing query performance.
- Learn optimization techniques, such as avoiding SELECT * and using appropriate indexes.
7. Transactions and ACID Properties:
- Understand the basics of transactions and their role in maintaining data integrity.
- Explore ACID properties (Atomicity, Consistency, Isolation, Durability) in database management.
8. Views and Stored Procedures:
- Create and use views to simplify complex queries.
- Learn about stored procedures for reusable and efficient query execution.
9. Security and Permissions:
- Understand SQL injection risks and how to prevent them.
- Learn how to manage user permissions and access control.
10. Advanced Topics:
- Explore advanced SQL concepts like window functions, CTEs (Common Table Expressions), and recursive queries.
- Familiarize yourself with database-specific features (e.g., PostgreSQL's JSON functions, MySQL's spatial data types).
11. Real-world Projects:
- Apply your knowledge to real-world scenarios by working on projects.
- Practice with sample databases or create your own to reinforce your skills.
12. Continuous Learning:
- Stay updated on SQL advancements and industry best practices.
- Engage with online communities, forums, and resources for ongoing learning and problem-solving.
Here are some free resources to learn & practice SQL 👇👇
Udacity free course- https://imp.i115008.net/AoAg7K
SQL For Data Analysis: https://news.1rj.ru/str/sqlanalyst
For Practice- https://stratascratch.com/?via=free
SQL Learning Series: https://news.1rj.ru/str/sqlspecialist/567
Top 10 SQL Projects with Datasets: https://news.1rj.ru/str/DataPortfolio/16
Join for more free resources: https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
1. Foundations:
- Learn basic SQL syntax, including SELECT, FROM, WHERE clauses.
- Understand data types, constraints, and the basic structure of a database.
2. Database Design:
- Study database normalization to ensure efficient data organization.
- Learn about primary keys, foreign keys, and relationships between tables.
3. Queries and Joins:
- Practice writing simple to complex SELECT queries.
- Master different types of joins (INNER, LEFT, RIGHT, FULL) to combine data from multiple tables.
4. Aggregation and Grouping:
- Explore aggregate functions like COUNT, SUM, AVG, MAX, and MIN.
- Understand GROUP BY clause for summarizing data based on specific criteria.
5. Subqueries and Nested Queries:
- Learn how to use subqueries to perform operations within another query.
- Understand the concept of nested queries and their practical applications.
6. Indexing and Optimization:
- Study indexing for enhancing query performance.
- Learn optimization techniques, such as avoiding SELECT * and using appropriate indexes.
7. Transactions and ACID Properties:
- Understand the basics of transactions and their role in maintaining data integrity.
- Explore ACID properties (Atomicity, Consistency, Isolation, Durability) in database management.
8. Views and Stored Procedures:
- Create and use views to simplify complex queries.
- Learn about stored procedures for reusable and efficient query execution.
9. Security and Permissions:
- Understand SQL injection risks and how to prevent them.
- Learn how to manage user permissions and access control.
10. Advanced Topics:
- Explore advanced SQL concepts like window functions, CTEs (Common Table Expressions), and recursive queries.
- Familiarize yourself with database-specific features (e.g., PostgreSQL's JSON functions, MySQL's spatial data types).
11. Real-world Projects:
- Apply your knowledge to real-world scenarios by working on projects.
- Practice with sample databases or create your own to reinforce your skills.
12. Continuous Learning:
- Stay updated on SQL advancements and industry best practices.
- Engage with online communities, forums, and resources for ongoing learning and problem-solving.
Here are some free resources to learn & practice SQL 👇👇
Udacity free course- https://imp.i115008.net/AoAg7K
SQL For Data Analysis: https://news.1rj.ru/str/sqlanalyst
For Practice- https://stratascratch.com/?via=free
SQL Learning Series: https://news.1rj.ru/str/sqlspecialist/567
Top 10 SQL Projects with Datasets: https://news.1rj.ru/str/DataPortfolio/16
Join for more free resources: https://news.1rj.ru/str/free4unow_backup
ENJOY LEARNING 👍👍
👍3
𝟭𝟬𝟬% 𝗙𝗿𝗲𝗲 𝗔𝗪𝗦 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗳𝗼𝗿 𝗔𝗯𝘀𝗼𝗹𝘂𝘁𝗲 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀😍
☁️ Want to Break Into Cloud Computing? Start Your AWS Journey for Free!📌
Cloud computing is one of the fastest-growing and highest-paying fields in tech. And Amazon Web Services (AWS) leads the way with over 30% of the global market share📊🎊
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3Skm0pM
Click below and start your cloud adventure today✅️
☁️ Want to Break Into Cloud Computing? Start Your AWS Journey for Free!📌
Cloud computing is one of the fastest-growing and highest-paying fields in tech. And Amazon Web Services (AWS) leads the way with over 30% of the global market share📊🎊
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3Skm0pM
Click below and start your cloud adventure today✅️
Here are some of the amazing Websites to Learn Python from Beginning to Advanced. 👇👇
1. LearnPython
🔗 Playlist Link
2. W3Schools
🔗 Playlist Link
3. Khan Academy
🔗 Playlist Link
4. FreeCodeCamp
🔗 Playlist Link
5. Sololearn
🔗 Playlist Link
1. LearnPython
🔗 Playlist Link
2. W3Schools
🔗 Playlist Link
3. Khan Academy
🔗 Playlist Link
4. FreeCodeCamp
🔗 Playlist Link
5. Sololearn
🔗 Playlist Link
Best python github Repositories very helpful for beginners -
1. scikit-learn : https://github.com/scikit-learn
2. Flask : https://github.com/pallets/flask
3. Keras : https://github.com/keras-team/keras
4. Sentry : https://github.com/getsentry/sentry
5. Django : https://github.com/django/django
6. Ansible : https://github.com/ansible/ansible
7. Tornado : https://github.com/tornadoweb/tornado
1. scikit-learn : https://github.com/scikit-learn
2. Flask : https://github.com/pallets/flask
3. Keras : https://github.com/keras-team/keras
4. Sentry : https://github.com/getsentry/sentry
5. Django : https://github.com/django/django
6. Ansible : https://github.com/ansible/ansible
7. Tornado : https://github.com/tornadoweb/tornado
GitHub
scikit-learn
Repositories related to the scikit-learn Python machine learning library. - scikit-learn
𝟱 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀😍
Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊
These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4iSWjaP
Job-ready content that gets you results✅️
Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊
These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4iSWjaP
Job-ready content that gets you results✅️
For data analysts working with Python, mastering these top 10 concepts is essential:
1. Data Structures: Understand fundamental data structures like lists, dictionaries, tuples, and sets, as well as libraries like NumPy and Pandas for more advanced data manipulation.
2. Data Cleaning and Preprocessing: Learn techniques for cleaning and preprocessing data, including handling missing values, removing duplicates, and standardizing data formats.
3. Exploratory Data Analysis (EDA): Use libraries like Pandas, Matplotlib, and Seaborn to perform EDA, visualize data distributions, identify patterns, and explore relationships between variables.
4. Data Visualization: Master visualization libraries such as Matplotlib, Seaborn, and Plotly to create various plots and charts for effective data communication and storytelling.
5. Statistical Analysis: Gain proficiency in statistical concepts and methods for analyzing data distributions, conducting hypothesis tests, and deriving insights from data.
6. Machine Learning Basics: Familiarize yourself with machine learning algorithms and techniques for regression, classification, clustering, and dimensionality reduction using libraries like Scikit-learn.
7. Data Manipulation with Pandas: Learn advanced data manipulation techniques using Pandas, including merging, grouping, pivoting, and reshaping datasets.
8. Data Wrangling with Regular Expressions: Understand how to use regular expressions (regex) in Python to extract, clean, and manipulate text data efficiently.
9. SQL and Database Integration: Acquire basic SQL skills for querying databases directly from Python using libraries like SQLAlchemy or integrating with databases such as SQLite or MySQL.
10. Web Scraping and API Integration: Explore methods for retrieving data from websites using web scraping libraries like BeautifulSoup or interacting with APIs to access and analyze data from various sources.
Give credits while sharing: https://news.1rj.ru/str/pythonanalyst
ENJOY LEARNING 👍👍
1. Data Structures: Understand fundamental data structures like lists, dictionaries, tuples, and sets, as well as libraries like NumPy and Pandas for more advanced data manipulation.
2. Data Cleaning and Preprocessing: Learn techniques for cleaning and preprocessing data, including handling missing values, removing duplicates, and standardizing data formats.
3. Exploratory Data Analysis (EDA): Use libraries like Pandas, Matplotlib, and Seaborn to perform EDA, visualize data distributions, identify patterns, and explore relationships between variables.
4. Data Visualization: Master visualization libraries such as Matplotlib, Seaborn, and Plotly to create various plots and charts for effective data communication and storytelling.
5. Statistical Analysis: Gain proficiency in statistical concepts and methods for analyzing data distributions, conducting hypothesis tests, and deriving insights from data.
6. Machine Learning Basics: Familiarize yourself with machine learning algorithms and techniques for regression, classification, clustering, and dimensionality reduction using libraries like Scikit-learn.
7. Data Manipulation with Pandas: Learn advanced data manipulation techniques using Pandas, including merging, grouping, pivoting, and reshaping datasets.
8. Data Wrangling with Regular Expressions: Understand how to use regular expressions (regex) in Python to extract, clean, and manipulate text data efficiently.
9. SQL and Database Integration: Acquire basic SQL skills for querying databases directly from Python using libraries like SQLAlchemy or integrating with databases such as SQLite or MySQL.
10. Web Scraping and API Integration: Explore methods for retrieving data from websites using web scraping libraries like BeautifulSoup or interacting with APIs to access and analyze data from various sources.
Give credits while sharing: https://news.1rj.ru/str/pythonanalyst
ENJOY LEARNING 👍👍
❤2👍2
𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗨𝗽𝗴𝗿𝗮𝗱𝗲 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝗜𝗻 𝟮𝟬𝟮𝟱😍
Explore top-notch courses to build expertise in cloud computing, data analysis, and visualization—all for FREE!
1. Microsoft Azure Fundamentals
2. Power BI Data Analyst Associate
3. Azure Enterprise Data Analyst Associate
4. Introduction to Data Analysis Using Excel (edX)
5. Analyzing & Visualizing Data with Excel (edX)
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3Phz4Li
Start learning today and transform your career! 🚀
Explore top-notch courses to build expertise in cloud computing, data analysis, and visualization—all for FREE!
1. Microsoft Azure Fundamentals
2. Power BI Data Analyst Associate
3. Azure Enterprise Data Analyst Associate
4. Introduction to Data Analysis Using Excel (edX)
5. Analyzing & Visualizing Data with Excel (edX)
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/3Phz4Li
Start learning today and transform your career! 🚀
❤1
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀😍
1️⃣ BCG Data Science & Analytics Virtual Experience
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics Virtual Internship
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/409RHXN
Enroll for FREE & Get Certified 🎓
1️⃣ BCG Data Science & Analytics Virtual Experience
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics Virtual Internship
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/409RHXN
Enroll for FREE & Get Certified 🎓
❤2
Data Analyst Interview Questions & Preparation Tips
Be prepared with a mix of technical, analytical, and business-oriented interview questions.
1. Technical Questions (Data Analysis & Reporting)
SQL Questions:
How do you write a query to fetch the top 5 highest revenue-generating customers?
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.
How would you optimize a slow-running query?
What are CTEs and when would you use them?
Data Visualization (Power BI / Tableau / Excel)
How would you create a dashboard to track key performance metrics?
Explain the difference between measures and calculated columns in Power BI.
How do you handle missing data in Tableau?
What are DAX functions, and can you give an example?
ETL & Data Processing (Alteryx, Power BI, Excel)
What is ETL, and how does it relate to BI?
Have you used Alteryx for data transformation? Explain a complex workflow you built.
How do you automate reporting using Power Query in Excel?
2. Business and Analytical Questions
How do you define KPIs for a business process?
Give an example of how you used data to drive a business decision.
How would you identify cost-saving opportunities in a reporting process?
Explain a time when your report uncovered a hidden business insight.
3. Scenario-Based & Behavioral Questions
Stakeholder Management:
How do you handle a situation where different business units have conflicting reporting requirements?
How do you explain complex data insights to non-technical stakeholders?
Problem-Solving & Debugging:
What would you do if your report is showing incorrect numbers?
How do you ensure the accuracy of a new KPI you introduced?
Project Management & Process Improvement:
Have you led a project to automate or improve a reporting process?
What steps do you take to ensure the timely delivery of reports?
4. Industry-Specific Questions (Credit Reporting & Financial Services)
What are some key credit risk metrics used in financial services?
How would you analyze trends in customer credit behavior?
How do you ensure compliance and data security in reporting?
5. General HR Questions
Why do you want to work at this company?
Tell me about a challenging project and how you handled it.
What are your strengths and weaknesses?
Where do you see yourself in five years?
How to Prepare?
Brush up on SQL, Power BI, and ETL tools (especially Alteryx).
Learn about key financial and credit reporting metrics.(varies company to company)
Practice explaining data-driven insights in a business-friendly manner.
Be ready to showcase problem-solving skills with real-world examples.
React with ❤️ if you want me to also post sample answer for the above questions
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
Be prepared with a mix of technical, analytical, and business-oriented interview questions.
1. Technical Questions (Data Analysis & Reporting)
SQL Questions:
How do you write a query to fetch the top 5 highest revenue-generating customers?
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN.
How would you optimize a slow-running query?
What are CTEs and when would you use them?
Data Visualization (Power BI / Tableau / Excel)
How would you create a dashboard to track key performance metrics?
Explain the difference between measures and calculated columns in Power BI.
How do you handle missing data in Tableau?
What are DAX functions, and can you give an example?
ETL & Data Processing (Alteryx, Power BI, Excel)
What is ETL, and how does it relate to BI?
Have you used Alteryx for data transformation? Explain a complex workflow you built.
How do you automate reporting using Power Query in Excel?
2. Business and Analytical Questions
How do you define KPIs for a business process?
Give an example of how you used data to drive a business decision.
How would you identify cost-saving opportunities in a reporting process?
Explain a time when your report uncovered a hidden business insight.
3. Scenario-Based & Behavioral Questions
Stakeholder Management:
How do you handle a situation where different business units have conflicting reporting requirements?
How do you explain complex data insights to non-technical stakeholders?
Problem-Solving & Debugging:
What would you do if your report is showing incorrect numbers?
How do you ensure the accuracy of a new KPI you introduced?
Project Management & Process Improvement:
Have you led a project to automate or improve a reporting process?
What steps do you take to ensure the timely delivery of reports?
4. Industry-Specific Questions (Credit Reporting & Financial Services)
What are some key credit risk metrics used in financial services?
How would you analyze trends in customer credit behavior?
How do you ensure compliance and data security in reporting?
5. General HR Questions
Why do you want to work at this company?
Tell me about a challenging project and how you handled it.
What are your strengths and weaknesses?
Where do you see yourself in five years?
How to Prepare?
Brush up on SQL, Power BI, and ETL tools (especially Alteryx).
Learn about key financial and credit reporting metrics.(varies company to company)
Practice explaining data-driven insights in a business-friendly manner.
Be ready to showcase problem-solving skills with real-world examples.
React with ❤️ if you want me to also post sample answer for the above questions
Share with credits: https://news.1rj.ru/str/sqlspecialist
Hope it helps :)
👍3
𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗦𝗸𝘆𝗿𝗼𝗰𝗸𝗲𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿😍
Whether you’re diving into AI, learning Python, mastering marketing, or sharpening your Excel skills📊
These free courses offer everything you need to stay ahead in tech, data, and business👨💻
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/49UMXbO
🔗 Start your learning journey today—absolutely free!✅️
Whether you’re diving into AI, learning Python, mastering marketing, or sharpening your Excel skills📊
These free courses offer everything you need to stay ahead in tech, data, and business👨💻
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/49UMXbO
🔗 Start your learning journey today—absolutely free!✅️
❤1👍1