Build a Career in Data Analysis with this Udacity Program
06 April 2023
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Course Overview
Become a Data Analyst course is designed to help improve your ability to program and work with messy datasets. It teaches learners to manipulate, prepare data for analysis, and create visualizations for data exploration. By taking this course, you will learn to use your data skills to tell a data-driven story.
The instructors including my teacher Sebastian Thrun, despite having varied teaching styles, displayed deep knowledge about every single concept.
"Doing this course helped me understand how to pull insights out of raw data by cleaning it, apply math and then visualize it."
- Arham Ansari
Course Structure
Firstly, the basic topics required for the course like SQL, Python, and Git were taught. This included a basic case study in Excel. Next, we were introduced to Python Pandas, Numpy, Matplotlib, and Scikit Learn with practical case studies and projects. Following that, Inferential Statistics was taken up where the instructor taught us about statistics and helped us work on a project for A/B testing. After that, there were sessions on data visualization, where the different types and techniques of presenting data were discussed.
Overall, the course has:
- End-to-end analysis of the data
- Hands-on learning with Python (Pandas, Matplotlib)
- Practical case studies for a better understanding of concepts.
Insider Tips
To get the best out of this course, I have included some important tips that you might find useful.
Create Text Files
You can create a text file where you can store and organize all the important Python functions in one place. This helps deal with topics like statistics which are tough to grasp.
Use References
Make sure to use more than one reference for understanding things, and do more case studies based on that. Also, remember to make notes of concepts in statistics.
Prerequisites
You should be familiar with concepts of Python specifically NumPy and Pandas.
Assessment
Assessments were taken in the form of 4 mini projects.
- The first project was the simplest, where we learned about the basic techniques of manipulating data in excel without using any programming language
- The second project was based on data cleaning, where we had to filter out the relevant data from raw data
- The third project was based on statistics, where we had to carry out mathematical operations using Python libraries.
- The fourth project was based on data visualization, where we had to do univariate and bivariate analysis and project results visually in graphs, charts, etc.
If the project reviewer is not satisfied with the submitted project, a re-submit request with proper guidance on needed changes will be sent to you.
Job Assistance
Udacity offers learners assistance in making their resumes and preparing for interviews.
Final Take
I am a software engineer who develops stock markets strategies based on real markets (open, high, low, and close) data. This course helped me understand how to pull insights out of raw data by cleaning it, apply math and then visualize it.
Data analysis is a growing field worldwide. You can also learn some front-end technologies and then apply for a software developer, junior data scientist role. Udacity has the world's best instructors. They also have separate free courses to learn Python. Once you have a thorough grasp of Python, you can maximize your learning from this course.
Key Takeaways
Work on Python data manipulation libraries such as NumPy and Pandas supervised learning models in real-world scenarios
Learn how to wrangle, explore, analyze, and communicate data as part of the data analysis process
Visually explore data at multiple levels to uncover insights and tell a compelling story
Learn how to use inferential statistics and probability to analyze A/B tests and build
Learn how to apply visualization principles to data analysis
Course Instructors
Arham Ansari
Software Engineer
Software Engineer with experience in working with Capital Markets and Fintech Industry.
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