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@Codingdidi

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Free learning Resources For Data Analysts, Data science, ML, AI, GEN AI and Job updates, career growth, Tech updates

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-------------Day-1 SQL---------- SQL is a standard language for accessing and manipulating databases. ✅What is SQL? - SQL stands for Structured Query Language - SQL lets you access and manipulate databases - SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987 ✅ What Can SQL do? - SQL can execute queries against a database - SQL can retrieve data from a database - SQL can insert records in a database - SQL can update records in a database - SQL can delete records from a database - SQL can create new databases - SQL can create new tables in a database - SQL can create stored procedures in a database - SQL can create views in a database - SQL can set permissions on tables, procedures, and views ✅✅ What Is a SQL Dialect, and Which one Should You Learn? -----MySQL----- MySQL is often compared to a handy free tool you might find in a toolbox. Imagine having a gadget that doesn't come with a price tag, yet is loved and recommended by many. That's MySQL for the digital world. https://www.instagram.com/reel/C9y0R6uyXxw/?igsh=dW5zZGNxbmRkcXUw Like for more❤️😍 Happy learning 🎊!

Check for these companies on LinkedIn to apply for these roles.

Below is a list of companies that are offering internships in the United Kingdom: SLB – Data Science Intern Tencent – NLP Research Intern Cohere – Research Intern Viridien – ML Intern Tencent – Data Product Intern Watchfinder – Data Engineer Intern

Swiss Re is hiring! Position: Data Analyst Qualification: Bachelor’s/ Master’s Degree Salary: 8 LPA (Expected) Experience: Freshers/ Experienced Location: Bangalore, India 📌Apply Now: https://careers.swissre.com/job/Bangalore-Data-Analyst-KA/1050003301/ Like for more ❤️ All the best 👍 👍

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.

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.

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.

Company: Gainwell Technologies! Position: Data Analyst Experience: Freshers/ Experienced https://jobs.gainwelltechnologies.com/job/Bangalore-Data-Analyst-KA-560100/1150924900/

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 👍❤️

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.

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

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.

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 👍👍

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https://www.instagram.com/reel/C8_W3eqSLqB/?igsh=eG82NTdjZWNwbmxt What'sapp +91 9910986344 to grab your seat.

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 👍👍

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”

✅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.

👉👉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]