This is great for others to hear. The tech field is open and many people, including me, are intimidated by it. Thanks for sharing

@TaniTech1111

11 ай бұрын

No need to be intimidated! Thanks for watching and thank you so much for subscribing- awesome!!🙏🏽

Hello Tani Tech, great video! Appreciate the share, please keep creating content like this!

@tialynn1111

11 ай бұрын

Thank you! Means so much, I will!

@ProjectHafidz

11 ай бұрын

@@tialynn1111 ❤

Very good work and I'm glad you are showing others how you made a way for yourself in data science.

@TaniTech1111

11 ай бұрын

Thank you!🙏🏽

you are insane!!! you have gone through so many courses & books and Mosh is awesome. I have been doing his SQL course. hopefully python afterwards!

@TaniTech1111

7 ай бұрын

Thats so awesome!!!! Mosh is so good!! I wish you much success and you will be successful if you keep your focus on what you desire!!! 2024 here we go!!🙏🏽

This is the best video of its kind. Thank you so much for sharing.

@TaniTech1111

6 ай бұрын

Thank you so much! Will add more soon!

Thanks for the good stuff, I'm a medicinal chemistry scientist and looking forward to become a data Scientst. I'm actually searching for role models like you for my future path. Thanks

@TaniTech1111

11 ай бұрын

Oh very good! I’ll be creating more valuable videos to help you on your path!

I got into tech same way without the masters. I did a lot of learning. I had a physics degree. The only thing is I made more mistakes and it took me longer to get a job I was software engineer at some point and pivoted to entry level data science role and now I’m set. It would be been helpful if I was on social media more.

@TaniTech1111

5 ай бұрын

Oh nice that’s excellent! I did actually get my masters but I also did extensive self study which ultimately helped a lot! Yes! You should share your story on socials! The world wants to hear from you!🙌🏾

Great information. Any advice for supply chain, transportation, and logistics management students wanting to have a more analytical foundation? Thanks in advance.

@TaniTech1111

10 ай бұрын

Thanks Kourtney! For students in supply chain, transportation, and logistics management who are looking to build a more analytical foundation, consider the following: 1. Develop Strong Quantitative Skills: Learn statistical analysis and data modeling. Become proficient with analytical software and tools like Excel, R, Python, and SQL to analyze, visualize, and interpret data. 2. Understand Data Analytics: Gain insights into predictive analytics, machine learning, and artificial intelligence, as these are increasingly used in the field for decision-making. 3. Learn Relevant Theories: Ensure that you have a solid understanding of relevant management, economic, and financial theories that underpin decision-making in supply chain and logistics. 4. Project Management: Build skills in project management to efficiently plan, execute, monitor, and close projects, ensuring they meet objectives and are delivered on time and budget. 5. Improve Decision-Making: Understanding decision analysis, including cost-benefit analysis and risk assessment, is crucial for evaluating alternatives and making informed decisions. 6. Knowledge of Supply Chain Technologies: Understand the technologies used in the supply chain, such as IoT, blockchain, and RFID, which can be applied for tracking, tracing, and managing goods and data. 7. Communication Skills: Develop your ability to communicate complex data findings in a clear and compelling manner to stakeholders who may not have your expert knowledge of data analysis. 8. Pursue Certifications: Consider obtaining certifications related to supply chain analytics and management from recognized institutions, such as APICS, to boost your credentials. 9. Real-world Experience: Seek internships, co-op positions, or project work that allows you to apply analytical theories to practical, real-world supply chain problems. 10. Network and Join Professional Organizations: Connect with professionals, join forums, and attend conferences to stay updated with the latest trends and developments in the field. Remember that the combination of theoretical knowledge, technical skills, and practical experience will position you well for a career in the analytics-intensive field of supply chain and logistics management.

Hi thank you for this!! It’s so informative :)) I am also similar to you right now, I have a degree in chemistry and have worked in labs after graduating. But I have worked for almost 2 years and for long term I feel like it would be great for remote working and living in a city (so I can also travel while doing my job - hard to do if you have to go to labs everyday) but I also want to be challenged and i like learning a lot so I’m interested in data science. However, I’m completely new to this and I want to maximise my efficiency in learning it since I plan to work while learning on the sideline. I want to work to fund my masters for this year hopefully !! But I have no experience in programming at all or anything related to computer science - and I like all of the recommendations you have done and will look into them. But for as a beginner; what first step should I take? Should I go through the stuff you recommended in order? For learning python- where is the best platform to learn this from? Thank you so much! I feel inspired and want to take on this challenge

@TaniTech1111

7 ай бұрын

Hi Kim! I will be creating a course very soon, but until then, there are several resources you can learn from, even python.org has tutorials. First of all, I’m so proud of you and it takes a lot of motivation to completely switch careers!💕 You will be rewarded generously as breaking into tech is one of the most lucrative careers you can get into! (And yes you can work remote 💕💕) You can easily learn Python 🐍, as it is a very straightforward language, you are very intelligent and I know you will do great! Stay tuned for my beginners course in the next month. If you cannot wait, please email me, or go through my recommendations within the video. wellnessdecoded1111@gmail.com

@kimchytingz

6 ай бұрын

@@TaniTech1111 Hi Tani, thank you for your kind words!! Honestly it took a lot for me to make this decision so it means a lot :) and I’m sure you understand how daunting it can be as well coming from a non CS background going into something like this. But I am determined to push through 💛 It makes me feel better knowing that you managed to crack through python so hopefully I can too 🤩 Okay, that’s awesome! I will look forward to your course!

Thanks for the video! Do you think it’s realistic to pivot into data science even if my bachelor’s degree isn’t in STEM? I like statistics (and was pretty good at it in high school). It’s been a while since I dabbled in it but I’m fully prepared to get my stats capabilities up to an advanced level. I’m also willing to work on certifications and towards a master’s degree if need be. I’m just hesitant to jump into all this hard work if the transition isn’t feasible. Any advice would be so helpful. Thank you!

@TaniTech1111

Ай бұрын

Hi could you tell me what your degree is in? It is most definitely possible to pivot into data science without a Bachelor in STEM. There are many options: Bootcamps Masters degree Self teaching --> creating a portfolio If you desire something, you will succeed 100% with persistence and determination. Let me tell you, breaking into tech is extremely extremely rewarding ✨

@SeasonedRookie

Ай бұрын

@@TaniTech1111 Thank you for the kind words. That’s so encouraging! I majored in writing with a minor in journalism. It would be a complete pivot for me.

One thing for sure is you have a very soothing voice

@TaniTech1111

9 ай бұрын

Thank you! 🙏🏽

That’s an amazing story. Were you in grad school while working full time?

@TaniTech1111

5 ай бұрын

Thank you! Yes I was! Grad school isn’t necessary though. A great bootcamp and solid portfolio will be more than sufficient🙏🏽

Thanks for sharing. Would you recommend to major in stats or just straight up data science?

@TaniTech1111

10 ай бұрын

Thanks for watching Statistics is really the foundation before the buzz word Data Science existed. To become a data scientist, you can major in either statistics or data science, but both options have their advantages: 1. Statistics: Majoring in statistics provides a strong foundation in mathematical and statistical concepts, which are essential for data analysis. You'll develop a deep understanding of probability, hypothesis testing, and statistical modeling. This background can be particularly valuable for certain data science roles that require advanced statistical analysis. 2. Data Science: A major in data science is more tailored to the specific skills needed for this field, including programming, machine learning, data visualization, and database management. It's a more practical approach that directly prepares you for the tasks commonly performed by data scientists. Your choice may depend on your interests and career goals. If you're more interested in the mathematical and statistical aspects of data analysis, a statistics major may be a better fit. If you prefer a broader skill set that includes programming and machine learning, a data science major could be the way to go. Additionally, you can always supplement your chosen major with relevant courses, certifications, and real-world projects to build a well-rounded skill set for a data science career. You really can’t go wrong with either/or and you will be very successful either way. At the end of the day, do some research and determine what best fits your goal. Thanks

Thanks for sharing... how do I prepare myself for the data science field during my graduation....i am from maths background not from computer science

@TaniTech1111

10 ай бұрын

Someone with a math background already has a solid foundation for a career in data science, as the field heavily involves statistical analysis and algorithmic processes. To build upon this and prepare for the data science field without a computer science background, consider the following steps: 1. Learn Programming: Begin with Python or R, which are widely used in data science. Utilize online platforms, courses, or books to get started. 2. Understand Data: Learn how to manipulate and analyze data. This includes understanding data cleaning, pre-processing, and visualization. 3. Study Machine Learning: Gain a solid understanding of machine learning algorithms and models. Use your mathematical knowledge to comprehend the underlying principles. 4. Dive into Data Analysis: Explore statistical methods and data analysis techniques, applying your mathematical background to understand and utilize various analytical models. 5. Develop Domain Expertise: Understanding the industry or domain in which you plan to work (e.g., finance, healthcare, retail) can be invaluable. It helps in forming relevant analytical approaches. 6. Work on Real Projects: Engage in practical projects, Kaggle competitions, or contribute to open-source data science projects to apply your knowledge and build a portfolio. 7. Understand Databases: Learn SQL and understand how to interact with databases to retrieve and handle data. 8. Improve Soft Skills: Enhance communication skills to explain technical findings to non-technical stakeholders effectively. 9. Stay Updated: Data science is a rapidly evolving field, so continuous learning is vital. Keep up with trends, tools, and techniques. 10. Network: Join data science communities, forums, and groups to network with professionals and learn from their experiences. Combining these steps with your mathematical knowledge will provide a robust foundation and enable you to build a career in data science.

can you give me a suggestion please. I want to pursue AI and ML. But before that I think of becoming a front end web developer , to have a part- time/freelance job for paying my expenses. Will there be a problem , that my web-designing job will affect my AI and ML learning journey ?

@TaniTech1111

9 ай бұрын

Hi Aswin! Thanks for watching and for the question: I would say that your plan to become a front-end web developer as a step towards pursuing AI and ML is practical and also strategic, especially for financial stability. I don’t think this will necessarily be a problem, in fact, there can be several benefits: 1. Transferable Skills: Skills you learn in web development, such as problem-solving, attention to detail, and understanding user experiences, are highly transferable to any tech-related field, including AI and ML. 2. Flexible Work: Freelance web development can offer a flexible schedule, allowing you to continue learning and working on AI and ML simultaneously. 3. Cross-Disciplinary Opportunities: Knowledge of both fields opens up unique opportunities. For example, you could end up working on AI-driven web applications, a niche that requires expertise in both domains. However, balancing the two could be challenging. Here are things to consider: 1. Time Management: Both fields are complex and require dedicated time for learning and practice. Balancing your work as a developer with rigorous study in AI/ML will demand strict time management and prioritization. 2. Learning Focus: While foundational programming skills are common between web development and AI/ML, the latter is math-intensive and involves specific paradigms and technologies. You might need extra effort to switch between the "creative" mindset of a web designer and the "analytical" mindset of machine learning. 3. Staying Updated: Both fields evolve rapidly, and staying current with the latest trends and technologies can be overwhelming. This is particularly true for AI/ML, given the pace of research and development. In conclusion, while your web development job won't hinder your journey into AI and ML, the key lies in maintaining a careful balance, staying committed, and managing your time effectively to keep learning and growing in both realms. Good luck! Both careers are extremely rewarding!!

@AswinBalaraman

9 ай бұрын

@@TaniTech1111 Thank you Very much for your time to giving me a deep insight.

Hi Tani, Thank you for the video. I am from a healthcare industry. Do you recommend i go to a bootcamp or getting my Masters

@TaniTech1111

6 ай бұрын

Hi Patrice, I obtained my masters, however, afterwards I realized you can break into the Data science field doing bootcamps and networking! So to conclude, you do not need a masters to break into the field at all. Boot camp will focus on the current l, fresh technologies in a small period of time. Research some bootcamps that offer a job after you successfully complete it! Good luck - let me know thanks!

@patricewilson4549

6 ай бұрын

@@TaniTech1111 Thank you so much for your response Tani!

I love your voice❤

@TaniTech1111

10 ай бұрын

Thanks and thanks for watching Eddy!

hey iam in final year want to pursue data science could you provide free resources

@TaniTech1111

7 ай бұрын

Hi Umer congrats! What do you wish me to provide? Thanks

@umerahmed7062

7 ай бұрын

The resources through which we can join in the field in short before hand knowledge of the field required

@TaniTech1111

7 ай бұрын

@@umerahmed7062 ok let me put this together and create a video this month

@umerahmed7062

4 ай бұрын

​​@@TaniTech1111have you created the video which you said that you will create

@tialynn1111

2 ай бұрын

@@umerahmed7062will work on it this month - you want a video on data science resources, correct?