Free SQL COURSES!!

https://www.instagram.com/reel/C8jA6lWSYOs/?igsh=MXVwdzdldzBrN204Mw==

Basic- course

1. Introduction to SQL

https://www.simplilearn.com/free-online-course-to-learn-sql-basics-skillup


2.Introduction-to-database-and-sql

https://www.mygreatlearning.com/academy/learn-for-free/courses/introduction-to-database-and-sql


3. My-sql-basics

https://www.mygreatlearning.com/academy/learn-for-free/courses/my-sql-basics


4. Oracle-sql

https://www.mygreatlearning.com/academy/learn-for-free/courses/oracle-sql

Advanced- Course

5.Advanced-tsql-querying-using-sql-2014

https://www.udemy.com/course/advanced-tsql-querying-using-sql-2014/


6. Sql-for-real-world-data-analysis

https://www.udemy.com/course/sql-for-real-world-data-analysis/

7. advanced-sql( text based)

https://www.kaggle.com/learn/advanced-sql


Share with credit https://t.me/codingdidi

✅✅FOLLOW @CODINGDIDI

𝐒𝐭𝐫𝐢𝐧𝐠 𝐌𝐚𝐧𝐢𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧:
Strings in Python are immutable sequences of characters.

𝟏- 𝐥𝐞𝐧(): 𝐑𝐞𝐭𝐮𝐫𝐧𝐬 𝐭𝐡𝐞 𝐥𝐞𝐧𝐠𝐭𝐡 𝐨𝐟 𝐭𝐡𝐞 𝐬𝐭𝐫𝐢𝐧𝐠.

my_string = "Hello"
length = len(my_string)  # length will be 5

𝟐- 𝐬𝐭𝐫(): 𝐂𝐨𝐧𝐯𝐞𝐫𝐭𝐬 𝐧𝐨𝐧-𝐬𝐭𝐫𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 𝐭𝐲𝐩𝐞𝐬 𝐢𝐧𝐭𝐨 𝐬𝐭𝐫𝐢𝐧𝐠𝐬.

num = 123
str_num = str(num)  # str_num will be "123"

𝟑- 𝐥𝐨𝐰𝐞𝐫() 𝐚𝐧𝐝 𝐮𝐩𝐩𝐞𝐫(): 𝐂𝐨𝐧𝐯𝐞𝐫𝐭 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐭𝐨 𝐥𝐨𝐰𝐞𝐫𝐜𝐚𝐬𝐞 𝐨𝐫 𝐮𝐩𝐩𝐞𝐫𝐜𝐚𝐬𝐞.

my_string = "Hello"
lower_case = my_string.lower()  # lower_case will be "hello"
upper_case = my_string.upper()  # upper_case will be "HELLO"

𝟒- 𝐬𝐭𝐫𝐢𝐩(): 𝐑𝐞𝐦𝐨𝐯𝐞𝐬 𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐚𝐧𝐝 𝐭𝐫𝐚𝐢𝐥𝐢𝐧𝐠 𝐰𝐡𝐢𝐭𝐞𝐬𝐩𝐚𝐜𝐞 𝐟𝐫𝐨𝐦 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠.

my_string = "   Hello   "
stripped_string = my_string.strip()  # stripped_string will be "Hello"

𝟓- 𝐬𝐩𝐥𝐢𝐭(): 𝐒𝐩𝐥𝐢𝐭𝐬 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐢𝐧𝐭𝐨 𝐚 𝐥𝐢𝐬𝐭 𝐨𝐟 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠𝐬 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐚 𝐝𝐞𝐥𝐢𝐦𝐢𝐭𝐞𝐫.

my_string = "apple,banana,orange"
fruits = my_string.split(",")  # fruits will be ["apple", "banana", "orange"]

𝟔- 𝐣𝐨𝐢𝐧(): 𝐉𝐨𝐢𝐧𝐬 𝐭𝐡𝐞 𝐞𝐥𝐞𝐦𝐞𝐧𝐭𝐬 𝐨𝐟 𝐚 𝐥𝐢𝐬𝐭 𝐢𝐧𝐭𝐨 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐬𝐭𝐫𝐢𝐧𝐠 𝐮𝐬𝐢𝐧𝐠 𝐚 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐞𝐝 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐨𝐫.

fruits = ["apple", "banana", "orange"]
my_string = ",".join(fruits)  # my_string will be "apple,banana,orange"

𝟕- 𝐟𝐢𝐧𝐝() 𝐚𝐧𝐝 𝐢𝐧𝐝𝐞𝐱(): 𝐒𝐞𝐚𝐫𝐜𝐡 𝐟𝐨𝐫 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐰𝐢𝐭𝐡𝐢𝐧 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐭𝐮𝐫𝐧 𝐢𝐭𝐬 𝐢𝐧𝐝𝐞𝐱.

my_string = "Hello, world!"
index1 = my_string.find("world")  # index1 will be 7
index2 = my_string.index("world")  # index2 will also be 7

𝟖- 𝐫𝐞𝐩𝐥𝐚𝐜𝐞(): 𝐑𝐞𝐩𝐥𝐚𝐜𝐞𝐬 𝐨𝐜𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐞𝐬 𝐨𝐟 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠.

my_string = "Hello, world!"
new_string = my_string.replace("world", "Python")  # new_string will be "Hello, Python!"

𝟗- 𝐬𝐭𝐚𝐫𝐭𝐬𝐰𝐢𝐭𝐡() 𝐚𝐧𝐝 𝐞𝐧𝐝𝐬𝐰𝐢𝐭𝐡(): 𝐂𝐡𝐞𝐜𝐤𝐬 𝐢𝐟 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠 𝐬𝐭𝐚𝐫𝐭𝐬 𝐨𝐫 𝐞𝐧𝐝𝐬 𝐰𝐢𝐭𝐡 𝐚 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐞𝐝 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠.

my_string = "Hello, world!"
starts_with_hello = my_string.startswith("Hello")  # True
ends_with_world = my_string.endswith("world")  # False

𝟏𝟎- 𝐜𝐨𝐮𝐧𝐭(): 𝐂𝐨𝐮𝐧𝐭𝐬 𝐭𝐡𝐞 𝐨𝐜𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐞𝐬 𝐨𝐟 𝐚 𝐬𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠 𝐢𝐧 𝐚 𝐬𝐭𝐫𝐢𝐧𝐠.

my_string = "apple, banana, orange, banana"
count = my_string.count("banana")  # count will be 2

Python pandas Complete
👇👇
https://topmate.io/codingdidi

Hope you'll like it

Like this post if you need more resources like this 👍❤️

Expand your job search to increase your chances of becoming a data analyst.

Here are alternative roles to explore:

1. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Focuses on using data to improve business processes and decision-making.

2. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Specializes in analyzing operational data to optimize efficiency and performance.

3. 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Uses data to drive marketing strategies and measure campaign effectiveness.

4. 𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Analyzes financial data to support investment decisions and financial planning.

5. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Evaluates product performance and user data to help product development.

6. 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Conducts data-driven research to support strategic decisions and policy development.

7. 𝗕𝗜 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Transforms data into actionable business insights through reporting and visualization.

8. 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Utilizes statistical and mathematical models to analyze large datasets, often in finance.

9. 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Analyzes customer data to improve customer experience and drive retention.

10. 𝗗𝗮𝘁𝗮 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝗻𝘁: Provides expert advice on data strategies, data management, and analytics to organizations.

11. 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Analyzes supply chain data to optimize logistics, reduce costs, and improve efficiency.

12. 𝗛𝗥 𝗔𝗻𝗮𝗹𝘆𝘀𝘁: Uses data to improve human resources processes, from recruitment to employee retention and performance management.


Hope this helps you 😊

Free website to learn and get certificates!!

https://panx.io/awesome-certificates/

❤️✅like more posts like these!!

🥳 🥳 Good news 🗞️🗞️ 🥳
I want to inform you that the MySQL classes 👩🏻‍🏫 will be starting from 10th July 🗓️ if you're interested please enroll in the classes ASAP 🔔 as there are limited seats 💺.
Thank you ☺️
Regards,
Codingdidi 👩🏻‍💻

Here's what you will learn!!

👉👉Template to ask for referrals(For freshers)

❤️Like for more ❤️

Hi [Name],

I hope this message finds you well.

My name is [Your Name], and I recently graduated with a degree in [Your Degree] from [Your University]. I am passionate about data analytics and have developed a strong foundation through my coursework and practical projects.
I am currently seeking opportunities to start my career as a Data Analyst and came across the exciting roles at [Company Name].

I am reaching out to you because I admire your professional journey and expertise in the field of data analytics. Your role at [Company Name] is particularly inspiring, and I am very interested in contributing to such an innovative and dynamic team.

I am confident that my skills and enthusiasm would make me a valuable addition to this role [Job ID / Link]. If possible, I would be incredibly grateful for your referral or any advice you could offer on how to best position myself for this opportunity.

Thank you very much for considering my request. I understand how busy you must be and truly appreciate any assistance you can provide.

Best regards,
[Your Full Name]
[Your Email Address]

✅What roles make it easier to get into Data Science?

Most of Data Scientists usually transitioned in from other roles

The most common ones, are - Data Analyst, Business Intelligence Engineer and Data Engineer.

For a fresher with only a bachelors degree, I would advise the Data Analyst role. Based on the team and work, you may in essence be able to work as a Data Scientist.

Follow this to optimise your linkedin profile 👇👇

Step 1: Upload a professional (looking) photo as this is your first impression

Step 2: Add your Industry and Location. Location is one of the top 5 fields that LinkedIn prioritizes when doing a key-word search. The other 4 fields are: Name, Headline, Summary and Experience.

Step 3: Customize your LinkedIn URL. To do this click on “Edit your public profile”

Step 4: Write a summary. This is a great opportunity to communicate your brand, as well as, use your key words. As a starting point you can use summary from your resume.

Step 5: Describe your experience with relevant keywords.

Step 6: Add 5 or more relevant skills.

Step 7: List your education with specialization.

Step 8: Connect with 500+ contacts in your industry to expand your network.

Step 9: Turn ON “Let recruiters know you’re open”

How to send follow up email to a recruiter 👇👇

Dear [Recruiter’s Name],

I hope this email finds you doing well. I wanted to take a moment to express my sincere gratitude for the time and consideration you have given me throughout the recruitment process for the [position] role at [company].

I understand that you must be extremely busy and receive countless applications, so I wanted to reach out and follow up on the status of my application. If it’s not too much trouble, could you kindly provide me with any updates or feedback you may have?

I want to assure you that I remain genuinely interested in the opportunity to join the team at [company] and I would be honored to discuss my qualifications further. If there are any additional materials or information you require from me, please don’t hesitate to let me know.

Thank you for your time and consideration. I appreciate the effort you put into recruiting and look forward to hearing from you soon.

Warmest regards,

(Tap to copy)

Like if helps

👍👍✅follow @codingdidi

All the best 👍👍

https://www.instagram.com/reel/C8_W3eqSLqB/?igsh=eG82NTdjZWNwbmxt

What'sapp +91 9910986344 to grab your seat.

Complete roadmap to learn data science in 2024 👇👇

1. Learn the Basics:
- Brush up on your mathematics, especially statistics.
- Familiarize yourself with programming languages like Python or R.
- Understand basic concepts in databases and data manipulation.

2. Programming Proficiency:
- Develop strong programming skills, particularly in Python or R.
- Learn data manipulation libraries (e.g., Pandas) and visualization tools (e.g., Matplotlib, Seaborn).

3. Statistics and Mathematics:
- Deepen your understanding of statistical concepts.
- Explore linear algebra and calculus, especially for machine learning.

4. Data Exploration and Preprocessing:
- Practice exploratory data analysis (EDA) techniques.
- Learn how to handle missing data and outliers.

5. Machine Learning Fundamentals:
- Understand basic machine learning algorithms (e.g., linear regression, decision trees).
- Learn how to evaluate model performance.

6. Advanced Machine Learning:
- Dive into more complex algorithms (e.g., SVM, neural networks).
- Explore ensemble methods and deep learning.

7. Big Data Technologies:
- Familiarize yourself with big data tools like Apache Hadoop and Spark.
- Learn distributed computing concepts.

8. Feature Engineering and Selection:
- Master techniques for creating and selecting relevant features in your data.

9. Model Deployment:
- Understand how to deploy machine learning models to production.
- Explore containerization and cloud services.

10. Version Control and Collaboration:
- Use version control systems like Git.
- Collaborate with others using platforms like GitHub.

11. Stay Updated:
- Keep up with the latest developments in data science and machine learning.
- Participate in online communities, read research papers, and attend conferences.

12. Build a Portfolio:
- Showcase your projects on platforms like GitHub.
- Develop a portfolio demonstrating your skills and expertise.


Resources for Projects
https://t.me/codingdidi

ENJOY LEARNING 👍👍