data analyst nanodegree

Do you find yourself thinking about being a data analyst? If yes, have you heard about Udacity Data Analyst Nanodegree Program

If you want to know more about this amazing program then this review article is the right place for you! 

This review article will help students to know details about the Udacity data analyst nanodegree program, its fee structure, pros and cons, and much more. 

Let’s dive right into it! 

Udacity Data Analyst Nanodegree is a program for data analysis for several aspiring students that want to pursue a career as a data analyst. 

The data analyst nanodegree program of Udacity helps students to learn all the important aspects and topics of data analysis.

Through this data analyst course, students will learn about working with Python along with its libraries like Numpy, pandas, Matplotlib and SQL which are essential for data analysis. 

Many students look forward to joining Udacity for its positive feedback from past students. This review article is the perfect place for you to solve your doubts

Udacity Data Analyst nanodegree

What type of Content and how many Projects are covered in Data Analyst Nanodegree by Udacity?

  • Course 1: Introduction to data analysis

This course helps the students to learn the various features of data analysis like data wrangling, data exploring, data analyzing, and data communication. 

Additionally, they will also learn to use Python and its libraries like pandas, Matplotlib, NumPy, etc for better data results. 

There are six lessons in this course: Anaconda, Jupyter Notebooks, Data Analysis Process, pandas and AND NumPy Case Study I & II, and Programming Workflow for Data analysis. 

In lesson one, students will discover the uses and management of Anaconda. They will also learn to imply the features of Anaconda to manage the packages of Python as well as use it in the Python environment. 

In lesson two, details of various Jupyter Notebook features like combining explanatory text, math equations, code, and visualizations will be covered. 

By learning these topics, the students will be able to combine all these elements in a single shareable document.  

Lesson three is crucial in understanding and managing the different steps of the data analysis process. 

In this process, they will also learn about using Python and its libraries like pandas in obtaining details from various datasets. 

Lessons four and five are case studies based on Python libraries for Machine Learning (pandas and NumPy). 

The case studies involve using a dataset where all the data analysis processes will be performed as well as data wrangling, exploring, analyzing, and visualization through the use of pandas and NumPy. 

Finally lesson six, students will learn methods to analyze data using command line interface and IPython. 

This course has two practical projects that help the students to get hands-on experience.  

  • Course 2: Practical Statistics

Practical statistics covers topics like applying supervised learning methods and A/B tests in practical experience. 

As the name suggests, this course is highly based on inferential statistics and probability. 

This course covers thirteen lessons: Simpson’s Paradox, Probability, Binomial Distribution, Conditional Probability, Bayes Rule, Standardizing, Sampling 

Distributions and Central Limit Theorem, Confidence Intervals, Hypothesis Testing, T-Tests and A/B Tests, Regression, Multiple Linear Regression, and Logistic Regression. 

The first lesson explains Simpson’s Paradox through the help of a case study. 

Whereas the next five lessons cover the fundamental explanation of the mentioned mathematical topics and their application in data analysis. 

Lesson 7-13 covers a more detailed analysis of various statistical methods which helps in understanding relations between variables and building different parameters and tools for correct data analysis. 

  • Course 3: Data Wrangling

This data analysis course deals with the features of data wrangling. The topics include gathering, assessing, and cleaning data. 

The students will also learn to apply the knowledge of Python in a systemic and programmatic manner for data analysis. 

There are four lessons in this course: Intro to data wrangling, gathering data, assessing data and cleaning data. 

In the first lesson, the students will get in-depth knowledge about features and processes of data wrangling like gathering, assessing and cleaning of data. 

Additionally, they will learn to download a CSV file using Kaggle with the help of data wrangling. 

Lesson two pinpoints the different sources through which learners can collect and analyze data. 

This includes web-scraping data and accessing data from APIs. They will also know the ways to install a file programmatically. 

This lesson covers the method to have different file formats like TSV, HTML files, TXT files, and JSON files into the Python library, pandas. 

The last topic covered is about keeping data using the PostgreSQL database.

Lesson three of this course delivers important information like accessing data programmatically and visually with the help of pandas, differentiating between content and structural data issues (dirty and messy data), and so on. 

It also teaches about knowing different data issues and categorizing them using validity, accuracy, completeness, consistency, and uniformity (metrics). 

Lastly, lesson four lives up to its name as it defines all the data cleaning process stages, methods using Python and panda to clean data, as well as using Python to test clean the code.

  • Course 4: Data Visualization with Python

Course 4 revolves around the principles of data visualization that is essential for data analysis. 

It is divided into seven lessons: Data Visualization in Data Analytics, Design of Visualization, Univariate Exploration of Data, Bivariate Exploration of Data, Multivariate Exploration of Data, Explanatory Visualizations, and Visualization Case Study. 

Each of these lessons deals with the various fundamentals, functions and features of data visualization like encoding, relationship between variables, categorization, annotations, plot types and so on. 

The last lesson is a case study where the students will be given a dataset involving the characteristics and prices of diamonds. They need to apply their data visualization skills in it. 

Important fact:  The projects for courses 3 and 4 are the same. It involves the collection of data from various sources which the learners need to access, categorize, determine its quality and clean it using Python. 

The documented record will be in Jupyter Notebook and shown through Python and SQL for visualization and analyses. 

udacity data analyst nanodegree projects:

Project I :

This project is based on analyzing the data of global and local temperatures and finally drawing a conclusion on trends of the data accessible. 

The students will learn about SQL and ways to download data from databases during the entire process. 

Project II:

This data analyzing project involves a dataset from Udacity which will be investigated by the students through the use of NumPy and pandas. 

The students will need to record all their data analysis processes which involve analyzing, finding and posing questions for the process and finally recording their outcomes and understanding. 

Project III:

The students will need to record their analysis and prepare a report that contains conclusions and feedback using statistical techniques based on the dataset provided to them for the experiment.  

About Instructors:

The Udacity Data Analyst Nanodegree Program instructors are well experienced with years of hands-on experience. 

Many of them have completed their masters and PhD from reputed universities and have worked with several renowned companies like Google, Galvanize, Facebook and so on.

Apart from him, there are several other talented and experienced instructors like Josh Bernhard, Derek Steer, Juno Lee, Mike Yi, David Venturi and Sam Nelson. 

How much money and time do I need to spend to complete the Data Analyst Nanodegree program?

The Udacity Data Analyst Nanodegree Program costs $310/month if you choose to enrol yourself on a monthly basis. 

You can complete the course in your own comfort zone as well as cancel the enrolment anytime according to your wish. 

There’s another option of paying for 4-month access to the data science course. Originally priced at $1243 for 4-month access, it’s now discounted and available for $1056 only. 

In this scheme, you will get to save an extra 15% if you give a 15% upfront payment. 

Within a span of 4 months, the course is designed to be completed. However, if you feel you need more time to complete the course, you can switch to the monthly access program.  

How to apply for Udacity Data Analyst Nanodegree program discounts?

The students can benefit from the current Covid-19 situation as Udacity is offering their data analyst nanodegree program at a heavy discount. 

I have received 75% on this course by entering the following details using the promo code. However, the discount percentage varies depending on the application of the user and how Udacity analyzes it. 

First, the students need to click on the link of the enrollment form and sign up. 

The next step requires them to fill out some of the basic details like their phone number, country, current working status, company size, and personal income. 

They need to enter the course in which they are interested to pursue and the reason behind their enrollment. 

After filling out the above details, they need to click on the Save & Submit option. 

Upon successfully receiving the application, Udacity will analyze and give personalized discounts based on the form. 

How to apply for Udacity Data Analyst Nanodegree Scholarships?

The Bertelsmann Technology Scholarship Program is aimed at reducing the financial burden of talented students. 

This way they can overcome the financial crisis and pursue their dreams of being a data analyst. 

This scholarship has provided financial assistance to over 50,000 students in the past 3 years. 

Anyone who is 18 years or above can apply for this scholarship. It is also essential that they at least have the basic knowledge of programming languages like Python and other technical terms. 

They also need to invest at least 3-5 hours/week for the Challenge Course and 5-10 hours/week for the Nanodegree Program. 

The application for the year 2020-21 is closed. Application for 2021-22 is expected to begin at the end of 2021. 

Interested students who want to know more about this scholarship or those who want to apply, can click here.

Some Tips to complete Data Analyst Nanodegree in less duration:

There are several tips that can be used to complete the Udacity Data Analyst Nanodegree Program within a month.  

With proper focus, determination and commitment, these tips are beneficial for students. 

However, it is important to note that if someone has ample time to complete the course then it is better to do it at a relaxed pace.

If you are still interested to do the course within a short period of time then these tips can be followed – 

  • Have prerequisite knowledge of basic topics like Python and its libraries, SQL, and so on. 

This helps to learn the course faster and develop projects and tools properly without any hassles. You can opt for Udacity’s free courses before officially enrolling on the data analyst nanodegree program

  • The students should build or develop programs, datasets or anything asked in the exercises right after finishing a lesson. 

Practically applying all the knowledge after learning each lesson ensures the concept is intact on the students’ minds and there isn’t any need to go back and keep on reading the same thing. 

  • It is always advisable to seek doubts and answers through the experiences of other students and past students of Udacity. 

The users can find relevant information through GitHub answers that would help them in completing their course faster and reliably.  Even Quora is a reliable source to ask questions and solve doubts. 

  • Investing leisure time effectively in completing this data analyst nanodegree program not only finishes the course before time but also gives the learners more time to clear their doubts and concepts in the later part. 

Who should enrol for the Udacity Data Analyst Nanodegree?

Anyone who is interested knows about data analysis or who wants to pursue a career as a data analyst can enroll on this course. 

This course is designed for students who are looking forward to learning and getting practical experience in handling Python, pandas, SQL, Matplotlib, data visualization, etc. 

They will get real-time practices that will enhance their knowledge and skills. 

Additionally, the instructors and mentors are supportive and reliable so the students can learn at ease. 

Udacity also helps to build resumes and cover letters for LinkedIn profiles and GitHub so learners will get many opportunities through this. 

Pros:

  • The quality of the course is excellent. It is partnered with companies like Google, Microsoft, Accenture, etc which delivers the best results.
  • Students get access to LinkedIn, GitHub and other platforms for their career support. 
  • Udacity provides cover letters, resumes that attract potential job offers.
  • Learners can also get expert consultation to sort their queries reliably.
  • The learning model is flexible so students can take their own time to understand properly and complete the course. 

Cons:

  • The price is expensive for this course. However, students wishing to enroll on the data analyst course can avail of a flat 75% discount using the promo code of our website. Click here
  • The mode of study is not portable as Udacity is not supported on mobile phones (Android or IOS). 
  • Students can’t access their course material once the course duration is over. 

Conclusion:

Overall, the Udacity data analyst nanodegree program is highly beneficial and recommendable to students across the globe for understanding data analysis and its impact. 

It develops the skills of an individual with its practical activities and projects. 

Although the course is on the expensive side, the personalized discount offer will help many students to get access to this program. 

If you have more to say about this program then connect with us on our social media handles like Facebook, Instagram, Twitter and so on. 

You can also drop a comment to sort your queries or to give us feedback!

Is Udacity Data Analyst Nanodegree worth it?

The Udacity Data Analyst Nanodegree Program is definitely worth it if you are seeking to learn about data analysis and want to secure a career in it. 

Its content contains in-depth research and knowledge about each of the topics which gives the learners a practical and easy to understand the experience. 

Additionally, the students will get access to the following – 

CLASS CONTENT

  • Content co-created with Kaggle
  • Real-world projects
  • Project reviews
  • Project feedback from experienced reviewers

STUDENT SERVICES

  • Technical mentor support
  • Student community

CAREER SERVICES

  • Resume support
  • Github review
  • Linkedin profile optimization

What are the prerequisites for Udacity Data Analyst Nanodegree?

A learner should have adequate knowledge of Python script, SQL, pandas, NumPy, Matplotlib and so forth for a better understanding of the program as it requires many practical activities. 

Interested students who don’t have the prerequisite knowledge can enroll Udacity on the free courses for proper knowledge. 

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