PTCL.Official

Experienced in data analytics, digitalization, and continuous auditing. Managed projects involving data analytics tools such as Power BI, Tableau, Python, SQL, and Excel with a proven track record of handling projects with millions of transactions per month.

✅ Designed and developed Sales Quality & Fraud dashboard with Power BI, SQL, Python, & MS Excel, analyzing over 8 million transactions monthly. 

✅ Implemented a churn prediction model using Python, Power BI, Teradata, and SQL. Analyzed 20+ factors to forecast early churn, achieving an 80% prediction success rate and reducing churn by 15% within one year.

✅ Developed a dynamic Churn Management dashboard utilizing Power BI for data visualization, Python, and SQL for exploratory data analysis (EDA), and SQL Server Management Studio (SSMS) for database management. 

✅ Implemented an Inventory Management dashboard using SQL Server Management Studio and Power BI to track modem collection from churned customers and inventory reutilization. Achieved a 20% increase in modem collection and a 15% improvement in inventory reutilization within 6 months.

✅ Implemented vehicle tracking dashboard & Gen-Set fuel optimization dashboard using Power BI, SQL, and Python, resulting in a 25% reduction in fuel-related frauds and improvements in site uptime and resource allocation optimization.

✅ Developed CHI trend analysis dashboard with Power BI & Python, analyzing 22 million data records to examine the 12-month CHI trend and identify churn patterns. Provided insights for rehab of the access network to boost sales.

✅ Conducted assignments focusing on sales fraud, churn, and network analysis. Identified frauds, revenue leakages, and recommended corrective actions using data analysis, cleaning, and visualization techniques, ensuring compliance and accuracy.

✅  Successfully managed TeamMate+ audit management portal, overseeing 100+ audit assignment. Automated audit follow-up and processes using TeamMate+, enhancing efficiency.

Manager Audit (Digitalization & Continuous Auditing) as Data Analytics & Digitalization Manager 

Applied data analytics, customer analytics, sales analysis, and business analysis skills to manage business operations, customer service, marketing, and technical operations, using PowerBI, Tableau, Excel, and SQL Server management studio.

Recognized with PTCL Business Excellence Award 2019 for the below data-driven initiatives.

✅ Led Business Operations & Sales team, delivering high-quality services to 16K+ customers and exceeding sales targets by 150% during Covid-19 using digital channels & CRM.

✅ Improved customer retention by 10%, DSL revenue by 15%, and smart TV revenue by 15% using data-driven customer experience initiatives, data visualization, and dashboard development.

✅ Increased data rates for 40% of DSL subscribers and converted 33% of ADSL subscribers to VDSL services using data analytics and CRM.

Assistant Manager (Business Operations & Analytics) 

Yobi

I provide marketing consulting and social media management services for Yobi, creating and sharing engaging content on social media to increase brand awareness and achieve Yobi’s business goals.

• Developing and implementing social media marketing campaigns based on the company’s goals, target audience, and industry trends

• Analyzing and reporting on the effectiveness of our marketing efforts and suggesting improvements based on the feedback and data

• Creating and managing a content calendar and a content library for each month, outlining the topics, formats, and dates of the content to be published on social media channels

• Researching and writing original and curated content for LinkedIn, Facebook, Instagram, X(formerly Twitter), Threads that include image posts, articles, infographics, and videos

• Publishing content on Yobi’s social media channels on a daily basis 

• Providing monthly reports on the key metrics, such as impressions, clicks, likes, comments, shares, followers, and conversions.

• A monthly report for each month, summarizing the results and insights of the content published on Social Media channels, along with the recommendations for the next month.

• Suggest and implement improvements based on the feedback and data.

Marketing Consultant & Social Media Expert

Hustlers Launchpad

Did you know that a whopping 80% of successful social media leads come from LinkedIn, while just 20% of sales professionals & businesses utilize it to sell.

Struggling to stand out in a crowded digital landscape and generate high-quality leads that convert?

Wondering how to effectively leverage Content Marketing, Sales Navigator, and Marketing Strategy to drive growth and success?

If you answered "yes" to any of these questions, you're in the right place!

🌟 Are you an Entrepreneur, Founder, CEO, Business Owner, Freelancer, Coach, or Consultant seeking Marketing, Content Marketing, and Sales Navigator expertise to drive sales and build a global audience? 

Look no further!

Welcome to my world of Content Marketing, Sales Navigator, and Marketing Strategy.

I am Ishtiaq Marwat, your dedicated LinkedIn Expert, Content Marketing Strategist & Sales Navigator Consultant who is passionate about helping individuals and businesses scale through strategic Content Marketing, Sales Navigator, and Social Media Marketing.

With over 6 years of experience, I have trained more than 2000 freelancers and entrepreneurs in my LinkedIn for Freelancing & Business Growth masterclass. 

My highly acclaimed Udemy courses have also impacted over 13,000 freelancers and business owners.

As a LinkedIn Expert & Sales Navigator Consultant, I have had the privilege of working with visionary Founders, CEOs, and startups. My journey has been marked by remarkable achievements, including devising content strategies, audience building, and driving client acquisition.

My content marketing strategies have played a pivotal role in generating millions of impressions, building audiences, and securing thousands of leads and clients through LinkedIn.

If you are ready to elevate your brand, generate sales, and build a thriving global audience.

Let's connect and explore how we can propel your business to new heights through strategic Content Marketing, Sales Navigator, and Marketing Strategy!

Founder (Content Marketing & Sales Navigator Expert)

I simplify Marketing Analytics for Entrepreneurs & Brands 👋 Follow for Digital Analytics, Content Marketing & Social Media Strategies

Hello, and thanks for coming here!!

I'm your Data Analytics go-to guy, with a knack for transforming raw data into actionable insights that drive business growth.

I am an experienced data analytics professional with over 7 years of expertise in leveraging BI tools such as PowerBI, Tableau, MS SQL Server Management Studio, and Microsoft Excel to transform data into valuable insights for business decision making and growth. 

✅ Experience:
✔ Over 7 years of total experience, specializing in Data Analytics, Continuous Auditing, Digitalization & Automation 
✔ 7+ years of experience in crafting dynamic data visualizations and insights using BI tools & Technologies such as PowerBI, Tableau, Python, Teradara, Sql Server and SQL.
✔ Led projects involving data analytics tools like Python,  SQL, and Excel, managing Big data analytics  and delivering actionable insights.
✔ Managed process automation, digitalization and continuous auditing initiatives, contributing to enhanced business efficiency and revenue growth.

✅ Skills:
✔ Proficient in BI tools/technologies: PowerBI, Tableau, Python, SQL, TeraData, SQL Server Management Studio.
✔ Skilled in data visualization, process automation, ETL/EDA techniques, SQL and Python programming for big data analytics & fraud detection.
✔ Experienced in project management, digitalization, and customer analytics.
✔ Strong in teamwork, negotiation, stakeholder management and collaboration, with excellent communication skills.

✅ Career highlights:

✔ Developed Sales Quality & Fraud dashboard using PowerBI, SQL, Python, SQL Server Management Studio & MS Excel, overseeing millions of transactions on monthly basis.
✔ Enhanced customer retention strategies by creating dynamic churn control & customer analytics dashboards using PowerBI, Python, SQL & Excel.
✔ Implemented Inventory Management and vehicle fuel tracking dashboards, providing real-time insights and optimizing operations.
✔ Streamlined audit follow-up processes, automating tasks and ensuring compliance and accuracy.

🤖 𝐄𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐥𝐥 𝐧𝐞𝐯𝐞𝐫 𝐛𝐞 𝐭𝐡𝐞 𝐬𝐚𝐦𝐞

The Apple Vision Pro is about to change how we learn in a big way.

What are your thoughts on this?

Credit: X/futureio
______
🤳 Contact us if you made a great AI tool to be featured: https://lnkd.in/d5VZ-W8H

#ai #tech #innovation 


Muhammad Ishtiaq Khan

Hello, and thanks for coming here!!

I'm your Data Analytics go-to guy, with a knack for transforming raw data into actionable insights that drive business growth.

I am an experienced data analytics professional with over 7 years of expertise in leveraging BI tools such as PowerBI, Tableau, MS SQL Server Management Studio, and Microsoft Excel to transform data into valuable insights for business decision making and growth. 

✅ Experience:
✔ Over 7 years of total experience, specializing in Data Analytics, Continuous Auditing and Digitalization.
✔ 4 years of experience in crafting dynamic data visualizations and insights using BI tools such as PowerBI, Tableau, and SQL.
✔ Led projects involving data analytics tools like Python and Excel, managing high transaction volumes and delivering actionable insights.
✔ Managed digitalization and continuous auditing initiatives, contributing to enhanced business efficiency and revenue growth.

✅ Skills:
✔ Proficient in BI tools: PowerBI, Tableau, TeraData, SQL Server Management Studio.
✔ Skilled in data visualization, ETL/EDA techniques, SQL and Python programming for analytics.
✔ Experienced in project management, digitalization, and customer analytics.
✔ Strong in teamwork and collaboration, with excellent communication skills.

✅ Career highlights:

✔ Developed Sales Quality & Fraud dashboard using PowerBI, SQL, Python, SQL Server Management Studio & MS Excel, overseeing 8.2 million transactions.
✔ Enhanced customer retention strategies by creating dynamic churn control & customer analytics dashboards using PowerBI, Python, SQL & Excel.
✔ Implemented Inventory Management and vehicle fuel tracking dashboards, providing real-time insights and optimizing operations.
✔ Streamlined audit follow-up processes, automating tasks and ensuring compliance and accuracy.

“I interviewed 17 people this week and no one was a fit.”

^^ a friend is telling me she can’t find good talent. 


If you interviewed 17 people and didn’t make an offer…

It's time to start looking in the mirror. 

Perfect candidates don’t exist.

If someone:

- Gets it
- Wants it
- Can do it

Give them a chance.

There are so many qualified individuals here on LinkedIn. 

But I see the same jobs being re-posted repeatedly, being left vacant for months. 

Instead of:

- Hire slow
- Fire fast

How about:

- Hire for attitude
- Fire for attitude

Who took a chance on you?  

It's time to repay the favor.

Social media has unique side effect of making everyone short term in their life. Making it hard for them to do anything that’s long term. Skills. Relationships. Wealth. Reputation. Health. Almost all long term endeavors are significantly harder for this dopamine junkie world.

I love Data Engineering!

As a Data Analyst for the past 7 years I find myself loving the work of Data Engineering more and more. I think there is actually a lot of crossover and overlap to Data Analysts as well.

If you can learn how to create simple pipelines from source databases or flat files to a SQL database that adds so much value. Most companies aren't dealing with petabytes of data so keeping things simple and working with things like SSIS, Azure Data Factory, or AWS Glue is a fantastic skill to learn.

Then working on Automations to automatically ingest and append or update that data is the next step.

I think the rise of Data Analysts + Data Engineers mixing to be Analytics Engineers will be a big thing in the future.

If “we need people who can hit the ground running” worked, companies would be drowning in AI billions. The last 8 years have shown that companies need people who continuously learn.

In 2012, companies needed people to hit the ground running with Big Data.
In 2014, they needed people with data science and deep learning skills.
In 2016, they needed ML engineering capabilities and NLP or CV experience.
In 2018, data engineering and MLOps were the significant skills gaps.
In 2022, it was Generative AI.
Today, they need people who can create more business value and reliable products.

For 12 years, companies have argued they don’t have time to train or upskill, but for 12 years, companies have really needed people who can upskill every 2 years.

How’s all that “hit the ground running” working for you? Let me guess, you’re still chasing data talent, trying to catch up.

#DataScience #DataEngineering

As Industry 4.0 reshapes our business landscape, it’s critical to grasp its diverse aspects. The "Periodic Table of Industry 4.0 Elements" serves as a high-level guide, focusing on crucial areas for companies to consider in their strategic planning.

𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐃𝐨𝐰𝐧 𝐭𝐡𝐞 𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐢𝐞𝐬:

𝟏. 𝐄𝐧𝐚𝐛𝐥𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: The major technological innovations that serve as the engine for Industry 4.0. Invest in upskilling your workforce with the proper digital literacy to effectively leverage these technologies for innovation and competitive advantage.

𝟐. 𝐕𝐚𝐥𝐮𝐞 𝐃𝐫𝐢𝐯𝐞𝐫𝐬: The primary benefits and objectives that Industry 4.0 aims to deliver. Prioritize and measure your initiatives based on their potential to drive value in these specific areas.

𝟑. 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: The most common use cases where enabling Industry 4.0 technologies change how companies operate and how employees work.

𝟒. 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: The most common use cases where products are being reimaged and improved with enabling Industry 4.0 technologies. Products are not only being designed differently, but designed with intelligence built in and customer experiences as part of the sale.

𝟓. 𝐍𝐞𝐰 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐌𝐨𝐝𝐞𝐥𝐬: Industry 4.0 introduces new ways of conducting business and providing value. Explore partnerships and platforms that could enable you to adopt new business models and expand your market reach.

𝟔. 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬: The foundational guidelines that enable the seamless integration and efficient functioning of advanced digital technologies and processes within the industrial ecosystem. 

This table is not exhaustive, but rather a focused lens to view the critical elements that can help drive strategic decisions during these transformative times. And just like the elements in nature, the elements of Industry 4.0 are vast and continuously expanding as we learn and discover new things!

💬 I'd love to hear your thoughts: How are you leveraging these elements in your Industry 4.0 strategy?

********************************************
• Follow #JeffWinterInsights to stay current on Industry 4.0 and other cool tech trends
• Ring the 🔔 for notifications!

𝗣𝘆𝘁𝗵𝗼𝗻 𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀 𝗖𝗼𝗻𝗰𝗲𝗽𝘁 𝗠𝗮𝗽 🐍

Data structures are a way of organizing data so that it can be accessed more efficiently depending on the situation. Data structures are fundamentals of any programming language around which a program is built.

Here is a Concept map to learn Data Structures in Python:

- 𝗟𝗶𝘀𝘁𝘀: Think of a digital shopping list – that's a Python list! 🛒📝 It holds various data types and allows easy addition, removal, and modification.

- 𝗗𝗶𝗰𝘁𝗶𝗼𝗻𝗮𝗿𝗶𝗲𝘀: Like a word-reference, Python dictionaries pair "keys" and "values". 📖🔑 Perfect for storing related info, akin to a contact list.

- 𝗧𝘂𝗽𝗹𝗲𝘀: Similar to lists, but unchangeable once set 🔒. Ideal for fixed values, like coordinates.

- 𝗦𝗲𝘁𝘀: Imagine a drawer with unique items – that's a set! ✨🗄️ Great for finding common elements.

- 𝗦𝘁𝗮𝗰𝗸𝘀: Visualize a stack of plates – last in, first out. 🥞⌛ Used for orderly retrieval.

- 𝗤𝘂𝗲𝘂𝗲𝘀: Picture a movie ticket queue – first come, first served. 🎫👥 Manages items in sequence.

- 𝗟𝗶𝗻𝗸𝗲𝗱 𝗟𝗶𝘀𝘁𝘀: Imagine linked chain links, each with data and a pointer. 🔗📜 Efficient for insertions and deletions.

Each structure has unique advantages, streamlining your code for efficiency. Remember, the choice depends on your goals!

👉 Follow Gina Acosta Gutiérrez 👩🏻‍💻 for more resources!

➡ Get the latest AI news, tools, tutorials and guides on using popular AI tools for FREE here: https://lnkd.in/ewfrvcy5

#python #data #datascience #machinelearning #ai #artificialintelligence #programming #dataanalysis #analytics #productivity #innovation #coding #tech #softwareengineer #developer #technology

Cleaning and Transforming data is one of the most time consuming parts of using data in the real world.

In this week's MySQL tutorial we dive into the basics of Data Cleaning with real tech layoff data.

Imagine a world where your thoughts, conveyed through natural language, get instantly translated into lines of code. 

There are an estimated 𝟐𝟔.𝟗 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 professional software engineers in the world as of 2022, up from 𝟐𝟏 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 in 2016. (Source: https://lnkd.in/ev97jpJ9). With the advancement of generative AI, programming languages are set to become as universal as traditional languages like English and Mandarin. 

While specialized programming languages and the need to master those languages won’t disappear, generative AI will bridge the gap, turning coding into a global language. This transformation will unlock the potential of nearly 8 billion people, empowering citizen programmers worldwide. 

𝐓𝐡𝐞 𝐩𝐨𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐚𝐫𝐞 𝐞𝐧𝐝𝐥𝐞𝐬𝐬:
𝟏. 𝐀𝐜𝐜𝐞𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲: Everyone, irrespective of their coding expertise, can contribute to software projects.
𝟐. 𝐃𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲: A broader pool of thinkers, dreamers, and problem solvers will emerge, enriching tech solutions with varied perspectives.
𝟑. 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲: Rapid prototyping and development will become the norm, accelerating innovation.

This transformation opens up a vast reservoir of untapped potential. Imagine a world where anyone, from a child with a game idea to a grandparent wanting to simplify a task, can shape technology using just their voice or text.

𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐢𝐬 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐚 𝐭𝐨𝐨𝐥; 𝐢𝐭'𝐬 𝐚𝐧 𝐢𝐧𝐯𝐢𝐭𝐚𝐭𝐢𝐨𝐧 – to thinkers, dreamers, and everyone in between, to co-create the digital future. And it's a future where programming is as natural as speaking!

𝐒𝐨𝐮𝐫𝐜𝐞 𝐟𝐨𝐫 𝐩𝐨𝐩𝐮𝐥𝐚𝐫 𝐩𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬:  https://lnkd.in/eGW6-QTg

********************************************
• Follow #JeffWinterInsights to stay current on Industry 4.0 and other cool tech trends
• Ring the 🔔 for notifications!

👋 Hi, my name is Avery. I have a Master's in Data Science, taught at MIT, and run a data analyst bootcamp... 
 
And I still Google basic Excel functions 🤷‍♂️ 
 
So if I still Google that... 
 
It's more than okay you do too 🤗

The SECRET to never choosing the wrong chart...the Bar Chart! Here are 18 options for your next bar chart.

HT: Rosa Mariana de León-Escribano for the inspiration

Tutorial and Tableau workbook - https://lnkd.in/eQ8nSyhi

Would anyone be interested in creating a Power BI version to share? Jason Thomas, maybe you?? Please :-)

18 Ways to Visualize Bar Charts

𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗦𝗤𝗟 𝗝𝗼𝗶𝗻𝘀: 𝗔 𝗖𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗖𝗵𝗲𝗮𝘁 𝗦𝗵𝗲𝗲𝘁! 🔍

SQL joins stand as a fundamental and potent tool in the arsenal of a database developer. They facilitate the merging of rows from two or more tables based on a related column, enabling the retrieval of data from multiple tables and revealing their interconnections.

Types of SQL Inner and Outer Joins:

- Inner Join: Retrieves rows from both tables where there is a match between the specified columns. This is the most commonly used type of join.

- Left Outer Join: Returns all rows from the left table and the matched rows from the right table. It's useful when you want to keep unmatched records from the left table.

- Right Outer Join: Returns all rows from the right table and the matched rows from the left table. It's beneficial for scenarios where unmatched records from the right table need to be preserved.

- Full Outer Join: Combines rows from both tables, whether they have a match or not. This join type ensures that no data is left behind, providing a comprehensive view of information across tables.

➡ Stay tuned and make sure to follow us at Data and AI Central 🚀 for more FREE resources!

#sql #data #machinelearning #ai #artificialintelligence #datascience #analytics #software #webdevelopment #developer #automation #technology #programming #coding #tech #learning

It took me 42 years to figure it out. Not all of it. Because nobody ever figures it all out. It took me 42 years to get there. But here is not a final destination. Because there is no there there. I remember sitting in my professor's office. He was an English professor. A writer. Once a poet, then an essayist. And he would tell me that I was in such a hurry. So obsessed with what came next. The next step. The next phase. The next chapter. 

And, in my defense, I was always so worried about what came next because I was poor. That's how college went. I'd work in the summer. Go back to school in the fall with a bit of money. Be flat broke by December. Work some random temp labor in the winter. Barely make it through the spring. Then make some more money in the summer. 

I always dreaded the winter. It wasn't just the evening all afternoon (blackbirds) and perpetual blue grey haze. It was running out of money. So I'd be at Cornell with my homie 🦾Ahmed Reza. And all our classmates would just be worried about studying and finals. Like good little students. And we'd be worried about "Shit, how are we going to buy groceries?". Still came out Phi Beta Kappa and shit. 

But it was like that. What's next. How am I going to survive. Where am I going to go. What am I going to do. What am I. What can I be. Where can I make my real stand in life. Shit, I need to make some money. Crisis. Back to stability. Back to crisis. 

Long-term progress is almost never linear. It bobs and weaves. We're always picking ourselves back up and starting from one again. But it's not actually from one (feels that way but it's not). We're starting from knowledge and experience. So we get back quicker. 

Took me 42 years just to get to a place in my life where I can be. For a long time, I needed to prove myself to the world. Well, first mostly to my dad. To prove that I wasn't trash. Needed to prove that I was worth something. That I was smart. That I was capable. That I was strong. But I eclipsed that long ago. Then it was just about proving it to me. 

Then it was just this incessant, pre-programed need to figure out the next, plan for it, know what will be, guard against it, be six steps ahead of it. And that sort of security is illusory. Nothing can stop the world. Nothing can stop the days and whatever comes will be. 

Said it before and I'll say it again: I am and was the get right man. Always trying to get it right. Line everything up. So I could just be. So I could just live. Finally made it. 

Keep the faith. Keep bobbing and weaving. Just keep going. 

No course, project, or degree can fully prepare you for your first few months on the job as an analyst. 

You will learn a million acronyms, obscure details of business processes you didn't know existed, and be exposed to databases far more complex that what you learned with. 

But no one is expecting you to be perfect. Remember to take a breath, ask questions (it's expected!), and embrace the puzzle of breaking the complexity into smaller parts. 

The growth you will experience technically and professionally during this time frame will amaze you!

#data #dataanalyst #firstjob

#ArtificialIntelligence #DataScience #MachineLearning 🎉👏🎉👏🎉
𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 𝗚𝘂𝗶𝗱𝗲 by THE LEGEND Gina Acosta Gutiérrez!

If you ever feel like the number of algorithms is overwhelming, you are not alone!  What we need is a great guide.  Fortunately, Gina has created one for us!

Includes all the following:

▶ 𝗦𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱

     ▶▶ 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
     ▶▶ 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻


▶ 𝗨𝗻𝘀𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱

     ▶▶ 𝗖𝗹𝘂𝘀𝘁𝗲𝗿𝗶𝗻𝗴
     ▶▶ 𝗔𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗶𝗼𝗻
     ▶▶ 𝗔𝗻𝗼𝗺𝗮𝗹𝘆 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻


▶ 𝗦𝗲𝗺𝗶-𝗦𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱

     ▶▶ 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻
     ▶▶ 𝗥𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻


▶ 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴

     ▶▶ 𝗠𝗼𝗱𝗲𝗹-𝗙𝗿𝗲𝗲
     ▶▶ 𝗠𝗼𝗱𝗲𝗹-𝗕𝗮𝘀𝗲𝗱

Enjoy,

T. Scott Clendaniel

#AI #BigData #DataMining #Programming #Technology #TScottClendaniel

TOP #AI/ #DataScience/ #MachineLearning Podcasts according to Data Science Dojo 😀 😊 😁 
 
 ▶     Data Skeptic
 ▶     Data Science Ethics
 ▶     Data Science At Home
 ▶     Data Crunch
 ▶     SuperDataScience
 ▶     Datacast

 ▶     Data Science Imposters
 ▶     Women In Data Science
 ▶     Linear Digressions
 ▶     Data Futurology
 ▶     Data Science In Production
 ▶     Cyentia Podcast

 ▶     Talk Python To Me
 ▶     O’Reilly Radar – The O’Reilly Data Show Podcast
 ▶     The Ai Podcast
 ▶     Datahack Radio
 ▶     Half Stack Data Science
 ▶     This Week In Machine Learning & AI (Twiml & AI)

Hands-on Data Science: Complete your First Project 🚀

This beginner crash course by Mısra Turp provides an introduction to the foundations of data science by solving real-life examples. This includes the different steps of a data science project, from setting the environment to loading and analyzing the data using Python, git, Jupyter Notebooks and other tools 👇🏼

📽️: https://lnkd.in/gYWwsXFT

#datascience #python #machinelearning #data

Credit Risk is a business problem that can be solved with data science. In 2 minutes, I'll break it down and share how to make Python and R credit risk projects for your target audience. 

Credit risk refers to the possibility that a borrower will fail to meet their obligations in accordance with agreed terms. 

This risk is primarily concerned with the likelihood that a lender may not receive the owed principal and interest, which leads to an interruption of cash flows and increased costs for collection. 

If the borrower defaults, the lender loses the amount lent and the interest due, potentially incurring further costs to recover these amounts.

Industries sensitive to credit risk:

1. Banking and Financial Services: Major global banks like JPMorgan Chase, Citigroup, and Bank of America have extensive operations focused on credit risk management.

2. Insurance Companies: Companies like Allianz, AXA, and State Farm deal with credit risk in their portfolios, particularly in their life insurance and annuities businesses.

3. Investment Firms and Asset Managers: Investment giants like BlackRock, Vanguard, and Fidelity manage substantial amounts of credit risk through their fixed-income investments.

4. Real Estate: Real estate firms, mortgage brokers, and developers like Toll Brothers and Lennar Corporation have to manage the risk of loan defaults.

Solving credit risk is the chief responsibility of the Data Science team. You can see example Python code and R code in this post. 

R Code: https://lnkd.in/evCsEUxf

Python Code: https://lnkd.in/ebZR6TtM

There you have it! Some good ideas to start improving developing Credit Risk models and design projects for your target audience. 

Ready to learn how to solve Business Problems with data science?

I’ve spent 100 hours consolidating my learnings into a free 5-day course, How to Solve Business Problems with Data Science. It comes with:

300+ lines of R and Python code 
5 bonus trainings
2 systematic frameworks
1 complete roadmap to avoid mistakes and start solving business problems with data science, TODAY.

👉 Here it is for free: https://lnkd.in/e_EkiuFD 

It took me 10 months to solve these business problems with data science. In the next 10 days, I'll share how I tackle them one by one (with examples). Here's what's coming:

1. Customer Segmentation
2. Demand Forecasting
3. Risk Management
4. Fraud Detection
5. Supply Chain Optimization
6. Marketing Optimization
7. Predictive Pricing Strategies
8. Churn Prediction and Retention
9. Business Process Automation
10. Product Development and Gaps

===

I’ve spent 100 hours consolidating my learnings into a free 5-day course, How to Solve Business Problems with Data Science. It comes with:

300+ lines of R and Python code 
5 bonus trainings
2 systematic frameworks
1 complete roadmap to avoid mistakes and start solving business problems with data science, TODAY.

👉 Here it is for free: https://lnkd.in/e_EkiuFD 

Taplio

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