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README.md

@@ -60,6 +60,37 @@ I will divide the resources into different levels of learning and will also prov
 
 **Interview Tip 1 💁**: While answering questions, try to explain in such a way that you're building your solution from base, if you know the answer, start with explaining how you reached to that answer, don't tell your answer, explain your thought process. Interviews wants to check your problem solving skills. Even if you give wrong answer but your thought process is correct, interviewer might be impressed.
 
+### Programming Languages & Data Structures and Algorithms 🖥️
+
+| Lecture Topics                      | Resources & Links                                                                                                                                                                                          |
+| ----------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Core Python                         | [Durga Sir Python](https://www.youtube.com/playlist?list=PLd3UqWTnYXOmzcSdWIh-EggqAtCXvJxzu), or [Corey Schafer](https://www.youtube.com/watch?v=YYXdXT2l-Gg&list=PL-osiE80TeTt2d9bfVyTiXJA-UTHn6WwU)      |
+| Intermediate Python                 | [Corey Schafer](https://www.youtube.com/watch?v=ZDa-Z5JzLYM&list=PL-osiE80TeTsqhIuOqKhwlXsIBIdSeYtc)                                                                                                       |
+| Advance Python                      | [Durga Sir Advance Python](https://www.youtube.com/watch?v=es457q7n3P8&list=PLd3UqWTnYXOkzPunQOObl4m_7i6aOIoQD)                                                                                            |
+| Core Software Engineering Principle | [Robust Python](https://www.amazon.in/Robust-Python-Write-Clean-Maintainable/dp/1098100662) & [Design Patterns](https://google.github.io/styleguide/pyguide.html)                                          |
+| Data Structures and Algorithms      | [Data Structures and Algorithms in Python](http://xpzhang.me/teach/DS19_Fall/book.pdf), [Introduction to Algorithms, MIT 6.006](https://ocw.mit.edu/courses/6-006-introduction-to-algorithms-spring-2020/) |
+
+**Learning Tip 2 💁**: If you're a beginner and learning python, it will require time to reiterate several times to understand a concept, & trust me it's totally worth it. As said learning Data science requires time and learning the hard way rather than shortcuts which will make you nowhere. So, don't get demotivated if you're not able to understand a concept, just keep trying and you'll get it.
+
+**Learning Tip 3 💁**: Data structures and algorithms is becoming one of the important topics in data science interview as well in giant companies, so it's important to learn it. Not only from the perspective of interviews, learning it and solving problems using dsa makes your problem solving skill and criticial thinking much more better than before and you will be having several tools in your toolbox to solve any problem. So I suggest to learn a particular topic and solve several questions on it, we will soon be adding several problems on this page to practice for data science.
+
+### Frameworks 📚
+
+| Topics     | Resources & Links                                                                                                                                                                                                                                                                                                                                                                                                                                          |
+| ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Pandas     | [Pandas user Guide](https://pandas.pydata.org/docs/user_guide/index.html#user-guide), [Getting started with Pandas](https://pandas.pydata.org/docs/getting_started/intro_tutorials/index.html),[Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyte, Book](https://www.pdfdrive.com/python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython-e158189564.html), [Data School](https://www.youtube.com/c/dataschool/videos) |
+| Numpy      | [Numpy Learn docs](https://numpy.org/learn/)                                                                                                                                                                                                                                                                                                                                                                                                               |
+| Matplotlib | [Matplotlib Tutorial](https://matplotlib.org/stable/tutorials/index.html), [Corey Schafer Matplotlib Tutorials](https://www.youtube.com/playlist?list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_)                                                                                                                                                                                                                                                                  |
+
+### Data Visualization & Analysis
+
+| Topics             | Resources & Links                                                                                                                                                                                                                                                               |
+| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Data Analysis      | [Python for Data Analysis](https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1491957662), [Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions](https://learning.oreilly.com/library/view/head-first-data/9780596806224/) |
+| Data Visualization | [Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures](https://clauswilke.com/dataviz/)                                                                                                                                                    |
+
+**Learning Tip 4 💁**: Learning frameworks is not a big deal, but the way you use frameworks to analyze data, visualize data and solve problems is what matters. So, I suggest to understand the CRUX of data analysis and data visualization and use the frameworks to build your solution. If you don't know the actual CRUX of data visualization, analysis, then there is no point in learning frameworks. and If you don't know how to work with data, then there is no point in learning ML.
+
 ## Core Data Science Fundamentals 🚀
 
 According to [Harvard business School](https://online.hbs.edu/blog/post/data-science-skills), Data science is the process of deriving meaningful insights from raw data. Data science aims to make sense of the copious amounts of data, also referred to as big data, that today’s organizations maintain.