In this Q&A session, I addressed concerns around the need for creativity in data visualization, how to stay consistent, how to apply learnings from Data courses to real-life use cases, and many others.
If you have any questions, put them in the comment section and I will respond to them ASAP!
Dive into the world of data analytics as we unleash the practical guide to doing it right! Discover powerful strategies, expert tips, and game-changing insights in this captivating episode that will elevate your analytics skills and career. Don't miss out on this data journey!
Data Analytics - How to Do it Right
In this first part of the discussion, Hamid Abdulsalam, a Data Scientist with Factual Analytics shared critical insights into how to get started as a Data Analyst.
Bringing over 8 years of experience as a Data Scientist and Statistician, he demystified the best strategy for gaining and retaining proficiency in Data Analysis.
We looked into the common misconceptions around Data Analysis and expatiated on the primary focus areas for rapid career growth in the Data Space.
Links mentioned by Hamid (https://www.linkedin.com/in/bigbirdhamid/) --
for publishing data content;
for learning data science concepts; https://towardsdatascience.com
Join us on this ride to discovery!
I briefly discussed the less technical requirement for becoming a Data Analyst/Scientist in this introductory episode. Anticipate subsequent live podcast interviews.
A look into data collection through webscrapping, using beautifulsoup and requests libraries in python.
While we gather momentum to learn some core python coding concepts; This episode albeit short seeks to clarify the need for python standalone files and to show the difference between Scripts and Modules in python.
Let me know your thoughts about this episode.
In this episode I bring the series on Collection Types to an end by discussing Tuples and Sets. I also talked about their importance and how to utilize them. Enjoy!
In this episode, I discuss the importance of Dictionary data structures and their methods. Quite an interesting episode this is!. Listen, make further research and apply this in your data transformation activities. Keep learning, growing, and leading!.
In this episode, I talked in-depth about the use of Lists and their importance to Data Science. If you find this insightful, feel free to share it with your network of Data Scientists and enthusiasts. More discussions on data structures will be aired in the coming episodes. Stay tuned!
In investigating a dataset for the purpose of transformation, visualization, or even for predictive modeling, it is almost inevitable to employ loops where a process is iterative or repetitive. This episode addresses just how loops fit into the mix!. Enjoy and stay tuned for the next episode.
In Data Exploration and Transformation, the importance of logical operation and conditional statements can not be over-emphasized. In this episode, I touched on the essential points needed to grasp the basic concept surrounding these. Enjoy and watch out for the next episode on Loops.
In this episode I discussed the significance of Python in the Data Science journey and what to look out for.
Enjoy the episode and endeavor to carry out personal studies. Practice! Practice !! Practice!!!
Here I talked about the importance of geoplots and how to use them effectively. Also made a summary of all we have covered so far about Data Visualization and storytelling. Watch out for the next series on Python.
Statistical insights are easily obtained via Distribution plots. Listen to find out more.
A quick look at the various composition plot types and how to use them to communicate data insights effectively. Enjoy!
Discussion on how to utilize Relation Plots for visualization.
An elementary look into the application of comparison plots.
A dive into Design practices and what makes a good visualization. Also discussed the different kinds of plots and where to suitably apply them. The next episode will entail a deeper dive, so stay tuned and geared up!
We discuss more on the Linear and Logistics regression and how they are essential in machine learning.
This episode introduces you to what machine learning is and the process involved.
