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 👍👍

Complete Python topics required for the Data Engineer role:

➤ 𝗕𝗮𝘀𝗶𝗰𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻:

- Python Syntax
- Data Types
- Lists
- Tuples
- Dictionaries
- Sets
- Variables
- Operators
- Control Structures:
- if-elif-else
- Loops
- Break & Continue try-except block
- Functions
- Modules & Packages

➤ 𝗣𝗮𝗻𝗱𝗮𝘀:

- What is Pandas & imports?
- Pandas Data Structures (Series, DataFrame, Index)
- Working with DataFrames:
-> Creating DFs
-> Accessing Data in DFs Filtering & Selecting Data
-> Adding & Removing Columns
-> Merging & Joining in DFs
-> Grouping and Aggregating Data
-> Pivot Tables

- Input/Output Operations with Pandas:
-> Reading & Writing CSV Files
-> Reading & Writing Excel Files
-> Reading & Writing SQL Databases
-> Reading & Writing JSON Files
-> Reading & Writing - Text & Binary Files

➤ 𝗡𝘂𝗺𝗽𝘆:

- What is NumPy & imports?
- NumPy Arrays
- NumPy Array Operations:
- Creating Arrays
- Accessing Array Elements
- Slicing & Indexing
- Reshaping, Combining & Arrays
- Arithmetic Operations
- Broadcasting
- Mathematical Functions
- Statistical Functions

➤ 𝗕𝗮𝘀𝗶𝗰𝘀 𝗼𝗳 𝗣𝘆𝘁𝗵𝗼𝗻, 𝗣𝗮𝗻𝗱𝗮𝘀, 𝗡𝘂𝗺𝗽𝘆 are more than enough for Data Engineer role.

Hiring for Computer Vision Professionals with the below skills

Required Skills :-
(i) 4 to 7 years of experience in Image processing and image analytics with computational capabilities, Scalable CV architecture with strong understanding of Image acquisition system (Camera, Lighting etc).
(ii) Tech Enthusiastic with signs of continuous learning of industry best practices in the domain of Image / Video processing.
(iii) Minimum 2 to 5 years of experience in C++ development.

Mandatory Skills :-
(i) C++
(ii) OpenCV
(iii) Keras, Tensorflow, Pytorch, Scikit-learn, Scikit-image

Interested candidates can share their profiles on the below email IDs,
omnishishankar.mishra@neilsoft.com
abhijeet.gupte@neilsoft.com
vaishnavi.rakhunde@neilsoft.com

How to enter into Data Science

👉Start with the basics: Learn programming languages like Python and R to master data analysis and machine learning techniques. Familiarize yourself with tools such as TensorFlow, sci-kit-learn, and Tableau to build a strong foundation.

👉Choose your target field: From healthcare to finance, marketing, and more, data scientists play a pivotal role in extracting valuable insights from data. You should choose which field you want to become a data scientist in and start learning more about it.

👉Build a portfolio: Start building small projects and add them to your portfolio. This will help you build credibility and showcase your skills.

𝐇𝐨𝐰 𝐭𝐨 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞 𝐘𝐨𝐮𝐫𝐬𝐞𝐥𝐟 𝐢𝐧 𝐚 𝐏𝐡𝐨𝐧𝐞 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰? [ Part-1]

𝐇𝐑: Hello, am I speaking with [Your Name]?

[Your Name]: Yes, this is [Your Name] speaking.

[Your Name]: May I know who is calling, please?

𝐇𝐑: Hi [Your Name], this is [HR's Name] from XYZ Company.

𝐇𝐑: I'm calling because you applied for the Data Analyst role at our company.

[Your Name]: Yes, that's correct. Thank you for reaching out.

𝐇𝐑: [Your Name], could you tell me a bit about yourself?

[Your Name]: Sure! I recently graduated with a bachelor's degree in [Your Degree] from [Your University]. During my studies, I developed a strong interest in data analytics, particularly in how data can drive decision-making and improve business outcomes.

In college, I took courses in statistics, data visualization, and programming, which gave me a solid foundation in data analytics concepts. I also completed an internship at [Internship Company], where I worked on [specific project or task], honing my skills in data analysis and gaining hands-on experience with tools like Excel, SQL, and Python.

Now, I'm eager to apply my knowledge and skills in a professional setting and contribute to XYZ Company's success. I'm particularly drawn to your company's innovative approach to [specific area related to the company's work] and believe that my background and enthusiasm for data analytics would make me a valuable addition to your team.

𝐇𝐑: That sounds great, [Your Name]! Thank you for sharing.

[Your Name]: Thank you for giving me the opportunity!


Like this post if you want me to continue this 👍❤️

Company: Gainwell Technologies!
Position: Data Analyst
Experience: Freshers/ Experienced

https://jobs.gainwelltechnologies.com/job/Bangalore-Data-Analyst-KA-560100/1150924900/

One day or Day one. You decide.

Data Science edition.

𝗢𝗻𝗲 𝗗𝗮𝘆 : I will learn SQL.
𝗗𝗮𝘆 𝗢𝗻𝗲: Download mySQL Workbench.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will build my projects for my portfolio.
𝗗𝗮𝘆 𝗢𝗻𝗲: Look on Kaggle for a dataset to work on.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will master statistics.
𝗗𝗮𝘆 𝗢𝗻𝗲: Start the free Khan Academy Statistics and Probability course.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will learn to tell stories with data.
𝗗𝗮𝘆 𝗢𝗻𝗲: Install Tableau Public and create my first chart.

𝗢𝗻𝗲 𝗗𝗮𝘆: I will become a Data Scientist.
𝗗𝗮𝘆 𝗢𝗻𝗲: Update my resume and apply to some Data Science job postings.

Here's the good news for you all .!

I'm starting two series on my Instagram channel from Wednesday 24th July.

1. SQL - reel will be at 11:00 am
2. Statistics -- reel will be posted at 6:30 pm


I need your support to make it ✅😍 more engaging.

Another good news is
From coming weekend

✓ Starting a logic building series on yt
✓ Along with the tableau series.

Let me know what you think or if there's something you wanna add on.