HOW TO GET & COMPLETE THE ALX-T DATA ANALYST NANODEGREE SCHOLARSHIP
The ALX Transforms Tech Program is a fully funded scholarship providing 20,000 Udacity Tech Nanodegree Programs for African youths to enable them to become future leaders in Tech.
These Nanodegree programs usually take 3 months and they include projects, virtual classroom sessions, as well as engagement with local and national employers.
The ALX-T Data Analyst Nanodegree prepares students for a career in Data Analytics by helping them learn to organize data, uncover patterns and insights, draw meaningful conclusions, and communicate critical findings. By taking this Nanodegree, you will develop proficiency in Python and its data analysis libraries (Numpy, pandas, Matplotlib) as you build a portfolio of projects to help you stand out in your job search. This program equips you with the required skills for an entry-level Data Analyst role.
Unfortunately, this scholarship is not available right now as the July cohort is the last cohort for 2022. The next cohort is in 2023. The good news is that you have time to prepare for the assessment. You can show interest in the next cohort on their website by filling out the email form here and clicking ‘I am interested’. When the next cohort application opens up, you will be notified immediately. You can also check their FAQ page here. You can check my article on other Udacity Nanodegrees Here.
APPLICATION PROCESS
Before applying, you need to go to the program website to confirm that you meet the below requirements:
· You are proficient in spoken and written English
· You have basic computer skills
· You have access to a laptop or desktop
· You have completed high school already
· You are between 18–35 years old
· You are originally from the African continent (current location isn’t a barrier).
· Knowledge & experience working with data using Python (Numpy & Pandas libraries) and SQL.
· You are willing to dedicate 10–15 hours per week to learning online and attending mandatory 2-hour weekly virtual sessions led by a Udacity Session Lead
Do you meet the above requirements?
If yes, then fill out the application form and take the multiple-choice assessment immediately after the form. This assessment covers SQL and Python Basics.
RESOURCES TO HELP YOU PREPARE FOR THE ASSESSMENT
The application is highly competitive as it is open to Africans all over the world, so you have to aim to get all the assessment questions right to be among the top candidates.
To pass this assessment, you need to be familiar with simple SQL Select statements and their respected outputs. You need to be familiar with SQL like operators, aggregates, join functions, etc. For the python questions, you need to be familiar with data types and operators, structures, control flow, functions, lambda, Numpy, Pandas libraries, string methods, and know how to add new tabs or lines to your code.
To cover these basics, I would recommend you use Udacity’s introductory courses for SQL and Python. When you eventually get the Data Analyst scholarship, it will show in your classroom that you have already taken these prerequisite courses.
If you are already familiar with basic SQL and Python, then you can prepare further by taking online practice assessments using practice sites like Hacker rank.
GETTING STARTED WITH THE NANODEGREE
Are you one of the lucky scholarship winners for the current cohort? Yay!, kudos for standing out from the crowd 👏.
You should know there is a possibility of your scholarship getting withdrawn if you do not meet the first project deadline and if you miss your connect sessions. You have 2 sessions every week, one is about your career and the other is about your learning progress.
Some persons may have to balance working, learning, and other things so completing this Nanodegree may be challenging. This is why you need to structure your learning plan.
ALX-T provides you with a timetable to help you plan your learning. You can follow theirs or tweak it to enable you to finish ahead of the deadline. Your reading timetable should be tailored based on your weekly schedule. Are you a student or an employee? How many hours can you dedicate weekly to learning? You need to put in at least 10 hours weekly to be able to meet project deadlines. I moved my timetable to my NOTION app in order to easily track my weekly deadlines and career sessions.
THE PROGRAM STRUCTURE
The program is divided into Core Curriculum and Extracurricular sections. You are required to complete 7 compulsory projects as seen below.
The Core Curriculum: This section consists of all the lessons and projects you need to complete to receive your certificate. Below are the sub-sections
1. Introduction to Data Analysis: This section introduces you to the tools required for the Nanodegree. It introduces you to the data analysis process using two different case studies. At the end of this section, you are expected to complete a project that meets the Udacity rubric requirements. In this project, you are to analyze a dataset of your choosing from Udacity options and then communicate your findings about it. You will need the Python libraries NumPy, Pandas, and Matplotlib for this project. This section should be completed within a month to prevent your scholarship from getting withdrawn. You shouldn’t panic about the projects, there are project guidelines and reviewers ready to help review your project and give you actionable feedback. Estimated by Udacity, it takes 23days to complete.
2. Data wrangling: This topic introduces you to data wrangling processes such as gathering, accessing data visually and programmatically, and cleaning quality and tidiness issues. You will be introduced to web scrapping, the process of cleaning data, merging tables, etc. In the end, you are expected to complete a data wrangling project where you will get to apply the different data gathering methods to gather data from a Twitter account, asses, clean, store, analyze and visualize the data. Estimated by Udacity, it takes 23days to complete this section.
3. Data visualization: Here, you will learn about visualization, univariate, bivariate, and multivariate exploration of data. You will also be introduced to explanatory data visualization before you are expected to complete a data wrangling project. You are to pick from Udacity project options or your dataset and perform exploratory analysis then create a presentation with explanatory plots to convey insights. Estimated by Udacity, it takes 31days to complete this section.
4. Career services: This entails videos and materials on how to write READMEs, collaborate with others on GitHub, and conduct industry research. In this session, you will also learn how to set up your GitHub, your LinkedIn profile, resume, and cover letter. Udacity reviewers help you review and provide feedback on your profiles. The reviews provided are actionable recommendations to help make your work better. I would advise you to take advantage of these sections as they help you through building the necessary documents you will need for every job application after completing your Nanodegree.
Extracurricular section: This section consists of extra lessons you can choose to complete to learn more. I would recommend you finish the core content first as you will have static access to the complete course content as long as you graduate. Below are the extracurricular sub-sections.
1. Intro to Machine Learning: This topic introduces you to machine learning concepts such as classification, algorithm, regressions, text learning, and a lot more. Estimated by Udacity, it takes 3days to complete.
2. Matrix Math and Numpy Refresher: Here, you will learn about matrix math to better understand building neural networks. Estimated by Udacity, it takes 45mins to complete.
3. SQL: This section takes you from SQL basics to advanced joins and performance tuning. It is the same as the free SQL course recommended earlier. It takes approximately 16hours to complete.
4. Python: This covers Python data types and operators, structures, control flow, functions, scripting, and Numpy and Pandas libraries. If your python basics are rusty, this will help as a refresher. It is the same as the free Python course recommended earlier. Estimated by Udacity, it takes 17hours.
5. Git and GitHub: This takes you through the basics from the definition of version control to tagging, branching, merging, and undoing changes on Git. You can take this Git course for free as well. Estimated by Udacity, it takes 10 hours.
TACKLING THE PROJECTS TO FINISH THIS NANODEGREE ON TIME
Here are some of the things I learned while taking the Nanodegree and I believe they will help you as you take it too.
1. Take advantage of the timetable you drafted. Learn daily if you can, stay consistent and follow through with your schedules to stay motivated and on track.
2. You shouldn’t be scared to make mistakes as there are Udacity reviewers to help review your work. No matter how many times you resubmit, they will give you actionable feedback until you get it right. There are session leads to help provide solutions to questions you might have. Udacity also has a question & answer forum and the forum mentors are especially helpful when you get stuck. You can search the forums to see if your problem is a common one (they usually are). If no luck? Then post a new question yourself. You should also get familiar with Google and Stackoverflow as you may need to do a lot of searching for code syntax and solutions to error codes.
3. Don’t be that person completing a Nanodegree without making new acquaintances. You should network while learning; there is a slack channel for Nanodegree students. There were times I got overwhelmed and didn’t feel like learning but I had a community that encouraged me. Aside from the slack channel, the All About the Data discord community has a channel for Udacity Nanodegree students to discuss. You can also find other learners via Twitter and LinkedIn and create a mini study group.
4. Do your projects well, share your progress online, and grow your portfolio. You can upload your projects to your GitHub, you can also write articles on your project findings and share them on medium. It might just be what someone else needs as motivation to continue their learning.
5. Avoid plagiarism. Whenever you use someone else’s code always reference it in your report. The Udacity projects have been done and uploaded by Udacity alumni so your reviewer will be able to tell if you plagiarized someone’s work, hence your project would be rejected. Try to be original with your projects; don’t just start by looking at people’s work.
6. Don’t miss connect sessions with your team leads, you will get to learn great career tips. In addition, the projects and other issues are tackled during those connect sessions.
7. Don’t compare your progress with others as we all learn differently and at different speeds. It is okay to go over a lesson more than once until you understand it. Don’t rush through, practice along with the instructor. You can’t learn how to code by using your eyes to watch someone else code. You learn by doing it yourself.
8. Don’t get discouraged that you don’t remember 100 percent of the lesson content, as you do your projects you will learn more.
9. To have static access to the classroom content, you need to finish all the core content and projects. Failure to finish, you will lose access to your classroom after a period.
Good luck 💪with your Data Analyst Nanodegree. You can follow me on Twitter and reach out whenever you feel stuck and need help. All Udacity projects I worked on can be found on my GitHub page.
