Udacity Programming for Data Science with Python Nanodegree Review 2024

Overview

Data Science is one of the most trending topics in the world of technology today. Data Science is not a single defining term, it is a combination of Math, Statistics, Advance Computing, Data Engineering, and some scientific methods.

Data Science is also related to Machine Learning, Big Data, and Data Mining. Data Science is used to extract useful or meaningful insights and information from a collection of Data or Datasets.

Jobs in the field of Data Science are increasing tangentially. There are various job roles in the field of Data Science such as Data Analyst, Data Architect, Business Analyst, Executive, and Data Scientist.

All these job roles hold respected and responsible positions in the industry. They are also paid above the market average. The role of Data Scientist and Data Analyst may become the most popular Job role by 2023 as predicted by the World Economic Forum.

There are various responsibilities that come with each tech role related to Data Science. As a Data Scientist, you will have to explore different data and their pattern to analyze the impact on an organization.

You will have to work with Statistics and some different programming languages for solving different problems. A similar kind of task and responsibilities are provided to roles such as Data Engineer or Data Analyst.

Becoming a Data Scientist is not that easy, it’s not an entry-level role, you need at least a year of experience or expertise in some skills to qualify for the role of Data Scientist in an interview.

There are some technical and Non-technical skills you require to practice and master to become a successful Data Scientist. You should have excellent knowledge of Computer Programming, Mathematics, and Statistics.

Technical knowledge such as programming, analysis tools, unstructured data workability while non-technical skills such as unstructured data workability are required for the role of Data Scientist.

This Udacity Programming for Data Science with Python Nanodegree review will help you a lot in understanding the course structure, its pros, and cons, syllabus, and duration.

The Udacity Programming for Data Science with Python Nanodegree is a complete package where you can learn the skills and technology required to become successful in the field of Data Science.

There are realistic projects which will help you to gain practical knowledge and understanding of industry standards such as investigating a database, exploring US Bikeshare Data, and Posting your work on GITHUB.

If you buy the course through the links in this article, we can earn some affiliate commission.  This helps us to keep OnlineCourseing up and running for your benefit.

About the Udacity Programming for Data Science with Python Nanodegree

Udacity Programming for Data Science with Python Nanodegree Program is a collection of courses, lessons, and realistic projects designed to enhance your skills and gain abundant knowledge to build a successful career in the field of Data Science.

Topics such as Structured Query Language, Python Programming, version controlling will be taught to you by world-class professionals. After learning these technologies, you will feel confident about implementing them in different areas of the industry.

This program provides you with everything you require to prepare for the Data Science Career.

Udacity is a trusted name and giant in online educational platforms aimed to help students and professionals to enhance and develop their skills to give a boost to their career with the help of various online courses related to programming or some other technical topics.

There is no specific prerequisite required for this Udacity Programming for Data Science with Python Nanodegree Program.

However, you should be well aware of performing basic tasks on a computer such as opening and closing files, copy and pasting, deleting files, etc.

This is just an introductory course providing the fundamental knowledge of SQL, Python Programming, and version controlling systems.

This Udacity Programming for Data Science with Python Nanodegree Program is for beginners who want to build a successful career in the field of Data Science, but don’t know where to start.

Udacity is a well-known platform in the field of online education and learning, they are popular for the top-rated instructors of their courses and programs, they provide valuable and useful content to any of the students and professionals trying to learn new skills.

After the completion of the Udacity Programming for Data Science with Python Nanodegree, you will be able to implement your knowledge of Data Science and Python Programming in detail.

For further research and exploration, you can also check this Udacity Data Scientist Nanodegree Review 2023: Your Way to Learn Data Science.

What was my motivation to enroll in Udacity Nanodegree?

There are more holes to be filled as technology is used by humans more and more. These gaps try to blur the distinction between man and machine by assisting one another in carrying out duties more quickly and easily.

Computer Science has always been my passion. Back in High School, I was known for my tech enthusiasm and top scores in programming classes. Later I obtained a bachelor’s degree in Information Systems from Haramaya University In July 2014, and I worked at Wolkite University as an Assistant Lecturer. In September 2016 I got two years of study leave from my employer and joined Addis Ababa University for a Master’s degree in Information Science and Systems (Language Technology). 

The Master’s program has been a unique experience for me because taking courses such as machine learning, computer vision, and machine translation enabled me to grasp the fundamental of data science and artificial intelligence. Furthermore, studying deep neural networks, image processing, computational linguistics, semantics, and language understanding gave me a whole new experience in the science of human language generation and understanding. 

Besides, I was able to attend and present my scientific papers and researches at different conferences, workshops, and summer schools. I attended and presented my thesis at the 32nd Neural Information Processing Systems Annual Conference, the world’s premier scientific meeting on neural computation, in 2018 in Montreal and the 33rd version of the same conference in 2019 in Vancouver. I have also attended and presented my scientific paper in LxMLS’2019 (the 9th edition of Lisbon Machine Learning Summer School)

I decided to apply for this Udacity program because I am sure it would strongly enrich my future studies and help me in my prospective career. Moreover, I consider this program as a great opportunity for hands-on, real-world, and cutting-edge programs, which includes projects before I made my transition from academia to the industry world, which hopefully would result in a better job.

Job Scenario

As we already discussed, Data Science is the most in-demand job field in 2023 and certainly in the upcoming future. Today tons and tons of Data are created by users all over the world on a daily basis as smartphones, laptops, and some other internet devices are easily accessible and affordable.

Various MNCs and companies hire data professionals to collect, clean, and process these data to extract out the meaningful and useful information from it which would help the companies to understand the future perspective of the industry and that’s the reason why there is an increase in the demand of the Data Science professionals.

The average salary earned by the Data Scientist in the US market is $96,216 per annum. It’s not an entry-level job, a good understanding of Mathematics, Statistics, Python Programming, and Database is required and that’s the reason why they are paid well in different parts of the world.

An entry-level Deep Scientist earns around Rs.8 to 15 LPA in the Indian market.

This complete Udacity Programming for Data Science with Python Nanodegree review will help you a lot in understanding the fundamentals of Data Science and Python Programming, its uses, scopes, and implementations.

Now we will cover each detail of this program, the features, advantages, and disadvantages so that you get to know the outcomes and the expectations from this Udacity Programming for Data Science with Python Nanodegree.

Costs and Duration

The overall duration of this Udacity Programming for Data Science with Python Nanodegree Program is 3 months and after enrollment, you have to give at least 10 hours per week to the program.

You should always give an appropriate time for learning fundamental skills and concepts of Data Science. This course is for beginners and does not require any kind of expertise is any skill but it’s your responsibility to level up yourself after the completion of the course and increase your knowledge in the field of Data Science.

You can enroll in the program and access the complete 3-month duration of the course for a reasonable price of $787.69.

However, if you want to pay monthly for the course then you can pay $309.10 per month and continue your learning with this Udacity Programming for Data Science with Python Nanodegree program.

Lastly, we always recommend you to stick to the date of completion and deadlines of the projects so that you don’t lag behind and make it an unusual time-consuming program.

My thoughts on course pricing

They gave me 79% off, and I think I paid a reasonable price for what I was able to learn. Without their discount, the original course price is a bit expensive.

Also, Read -> My Experience with Udacity Nanodegrees.

Prerequisites for Udacity’s Programming for Data Science with Python Nanodegree

Coming to the prerequisites of this Nanodegree program, there is no prior knowledge of programming required. This course is perfect for beginners as they will be introduced to SQL and Python Programming with libraries such as Pandas and NumPy. 

Version controlling systems specially GitHub will be taught to students so that they get to know how the industry works by saving, tracking, and collaborating with others with the help of GIT.

There is no prior knowledge of programming and mathematics required, but you should have basic knowledge or experience of working on laptop or desktop systems.

You should be comfortable in performing various basic operations such as opening files and folders, copy-pasting, deleting files, etc.

It is always good to have basic knowledge of computers, mathematics, and statistics and if you already have the prerequisites then congrats, you are ready to rock and enroll yourself in the Udacity Programming for Data Science with Python Nanodegree and learn some important and valuable skills. 

Must see -> Udacity AI programming with Python Nanodegree Review 2022: Learn AI with Udacity

Syllabus of Udacity’s Programming for Data Science with Python Nanodegree

Talking about the syllabus of the Udacity Programming for Data Science with Python Nanodegree Program, it will clear all the basics and doubts of a beginner trying to get into the field of Data Science.

The entire syllabus is divided into 3 courses where each of the courses has its own importance in developing your Data Science skills, the courses have various lessons along with challenging projects to practice your learning and implementations.

The projects in this Nanodegree program are enough to evaluate the knowledge and information you gained in the program.

So, for now, let’s go in-depth with the details of every chapter and lesson in the Udacity Programming for Data Science with Python Nanodegree program.

Course 1: Introduction to SQL

So this will be the first course of your Udacity Programming for Data Science with Python Nanodegree Program and in this course, you will learn SQL fundamentals such as Aggregations, JOINs, and Subqueries.

You will also learn to answer complex business problems with the help of SQL.

Course 1 of the Nanodegree program consists of four lessons. So, let’s dive into the details of each lesson.

Lesson one is Basic SQL. In this lesson you will write common SQL commands such as SELECT, FROM, and WHERE. You will also learn to use logical operators such as LIKE, OR, and AND.

Lesson two is SQL Joins. In this lesson you will learn to write JOINs in SQL, you will use this to combine data from multiple resources to answer various complex business questions.

Lesson three is SQL Aggregations. In this lesson, you will learn about the common aggregations in SQL including COUNT, MIN, MAX, and SUM.

You will also learn to write CASE and DATE functions, as well as work with NULLs.

Lesson four is Advanced SQL Queries. In this lesson, you will learn to use subqueries also known as CTEs in various situations.

You will also learn to use other window functions such as RANK, LAG, LEAD, NTILE, and practice new functions along with dividing complex tasks.

After the completion of all these lessons of course 1, now it’s time for you to work on a project. The project of this course is to investigate a Database, in this project you will work with the relational database with the help of PostgreSQL.

You will be completing the entire data analysis process starting by posing a question, running appropriate SQL queries to answer different questions, and finishing it by sharing your findings.

Course 2: Introduction to Python Programming

In this part of the Nanodegree Program, you will learn Python Programming and use it to represent and store data using different data types and variables.

You will also learn to use conditionals and loops to control the flow of your program. You will learn to use different data structures such as lists, sets, tuples, and dictionaries to store collections of related data. 

In this course, you will define and document your own custom functions, write scripts, and handle errors. In advance, you will also learn to use two powerful python libraries, NumPy and Pandas.

NumPy is a scientific computing package, while Pandas is a data manipulation package.

This course 2 of the Nanodegree Program is divided into 7 lessons to elaborately explain the concepts in a precise manner. So, let’s check the details of the lesson available in this course.

Lesson one is Why Python Programming. In this lesson, you will get a brief overview of what you will learn throughout the course. You will also learn and understand why you should learn to program with Python. 

Lesson two is Data Types and Operators. In this lesson, you will learn to represent data using different data types in Python such as integers, floats, booleans, lists, tuples, sets, dictionaries, and some compound data structures.

You will also learn to perform computation and create logical statements using Python operators such as Arithmetic, Assignment, Comparison, Logical Membership, and Identity. You will declare, assign, and reassign values using Python variables. 

In addition, you will also learn to modify values using built-in functions and methods with practicing whitespace and style guidelines.

Lesson four is functions. In this lesson, you will learn to create your own functions. You will create and reference variables using the appropriate scope and add documentation to functions using docstrings.

You will also learn to define lambda expressions to quickly create anonymous functions. You will use iterators and generators to create a stream of data.

Lesson five is Scripting. In this lesson, you will set up your Python Programming environment.

You will learn to run and edit python scripts, interact with raw input from users, identify and handle different errors and exceptions in your code, find and use modules in Python Standard Library and third-party libraries.

You will also perform an experiment in the terminal using a Python Interpreter.

Lesson six is NumPy. In this lesson, you will learn about NumPy which is a scientific computing package and also a Python library.

You will learn to create, access, and modify multidimensional NumPy arrays also known as ndarrays. You will learn to use slicing, boolean indexing, and set operations to select or modify subsets of ndarrays. In addition, you will also learn to use broadcasting to perform operations on “ndarrays” of different sizes.

Lesson seven is Pandas. In this lesson, you will learn about Pandas which is a kind of Data manipulation package, also a Python Library.

In this lesson, you will learn to create, access, and modify the main objects in Pandas, Series, and DataFrames. You will perform arithmetic operations on Series and DataFrames.

You will learn to load data into DataFrame and deal with Not a Number (NaN) values.

So, after the completion of all these lessons of the course, again it’s time for you to work on the project. The project of this course is to Explore US Bikeshare Data.

In this project, you will use Python to answer interesting questions about bike share trip data collected from three U.S cities.

You will write code to collect the data, analyze and compute descriptive statistics, and create interactive experiences in the terminal that provide answers to your questions.

Course 3: Introduction to Version Control

So this will be the last course of this Nanodegree Program and in this course, you will learn how to use version control to track and share your work with other people in the data science industry.

This third course of the Nanodegree Program is divided into 7 lessons to broadly classify and explain the concepts precisely. So let’s uncover the details of every lesson available in this course.

Lesson one is Shell Workshop. In this lesson, you will learn about Unix shells, which is a kind of powerful tool for developers of all sorts. You will get a quick introduction to the basics of using your locale computer system.

Lesson two is Purpose and Terminology. In this lesson, you will learn why developers use version control and practice version control in your daily life.

You will get an overview of essential Git vocabulary. You will learn to configure and use Git using the command line.

Lesson three is to Create a Git Repo. In this lesson, you will practically learn and create your first git repository with git init.

You will copy an existing Git repository with a git clone. You will learn to review the current state of a repository with powerful git status.

Lesson four is Review a Repo’s History. In this lesson, you will review a repo’s commit history git log.

You will customize the git log’s output using command line flags in order to reveal more information about each commit. You will learn to use the git show command to display just one commit.

Lesson five is Add Commits to a Repo. In this lesson, you will learn and master the git workflow. You will make commits to an example project.

You will use git diff to identify what parts of a file have been changed in a commit. You will also learn how to mark files as “Untracked” using .gitignore.

Lesson six is Tagging, Branching, and Merging. In this lesson, you will learn about Tagging, Branching, and Merging. You will learn to Organize your commits with tags and branches.

You will learn to jump to particular tags and branches using git checkout and at last, you will learn how to merge changes on different branches and crush the pesky merge conflicts.

Lesson seven is Undoing Changes. This will be the last lesson of your course and the Udacity Programming for Data Science with Python Nanodegree Program.

In this lesson, you will learn how and when to edit or delete an existing commit. You will use the git commit -amend flag to alter the last commit. You will also learn to use git reset and git revert to undo and erase commits.

So after the completion of all these lessons of this Course 3 module of the Nanodegree program, it’s time for you to work on some hands-on projects to gain more practical exposure.

The project of this course is to Post your work on GitHub. In this project, you will learn to use the common tools for programmers, such as Git and terminal.

You will post two different versions of Jupyter Notebook capturing your learnings from the course and add a commit to the git repo of your project. 

How was the project experience?

The project were challenging and interesting. Now you have to apply all the elements you have grasped in one succinct way, which is quite different from the simple lesson-specific exercises. The project reviews I had were personalized and worth the effort. The two main projects are working with Relational Database in SQL and Exploring US Bike share data with Python.

Investigate Relational Database

In this project, I used SQL to explore a database related to movie rentals. I wrote SQL code to run SQL queries and answer interesting questions about the database. As part of the project submission, I ran SQL queries and build visualizations to showcase the output of the queries

In this project, I made a query on the Sakila DVD Rental database. This database holds information about a company that rents movie DVDs. For this project, I was querying the database to gain an understanding of the customer base, such as what the patterns in movie watching are across different customer groups, how they compare on payment earnings, and how the stores compare in their performance. The schema for the DVD Rental database is provided as below.

Question 1

We want to understand more about the movies that families are watching. The following categories are considered family movies: Animation, Children, Classics, Comedy, Family, and Music. Create a query that lists each movie, the film category it is classified in, and the number of times it has been rented out.

Question 2

Now we need to know how the length of rental duration of these family-friendly movies compares to the duration that all movies are rented for. Can you provide a table with the movie titles and divide them into 4 levels (first_quarter, second_quarter, third_quarter, and final_quarter) based on the quartiles (25%, 50%, 75%) of the rental duration for movies across all categories? Make sure to also indicate the category that these family-friendly movies fall into.

Question 3

Finally, provide a table with the family-friendly film category, each of the quartiles, and the corresponding count of movies within each combination of film categories for each corresponding rental duration category. The resulting table should have three columns:

• Category
• Rental length category
• Count
• Explore US Bike share data

In this project, I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. I wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.

To complete this project, the following software requirements applied

• You should have Python 3, NumPy, and pandas installed using Anaconda
• A text editor, like Sublime or Atom.
• A terminal application (Terminal on Mac and Linux or Cygwin on Windows).

The Datasets

Randomly selected data for the first six months of 2017 were provided for all three cities. All three of the data files contain the same core six (6) columns:

• Start Time (e.g., 2017-01-01 00:07:57)
• End Time (e.g., 2017-01-01 00:20:53)
• Trip Duration (in seconds – e.g., 776)
• Start Station (e.g., Broadway & Barry Ave)
• End Station (e.g., Sedgwick St & North Ave)
• User Type (Subscriber or Customer)

The Chicago and New York City files also have the following two columns:

• Gender
• Birth Year

Data for the first 10 rides in the new_york_city.csv file

            

Statistics Computed

I wrote code to provide the following information’s:-

#1 Popular times of travel (i.e., occurs most often in the start time)

• most common month
• most common day of week
• most common hour of day

#2 Popular stations and trip

• most common start station
• most common end station
• most common trip from start to end (i.e., most frequent combination of start station and end station)

#3 Trip duration

• total travel time
• average travel time

#4 User info

• counts of each user type
• counts of each gender (only available for NYC and Chicago)
• earliest, most recent, most common year of birth (only available for NYC and Chicago)

                              Python Project code screenshot

My thoughts on the course timeline

I had to commit more than 4 hours per day because if you don’t finish within the timeline I would have to pay again. I think as long as you paid, it should allow you to go take the program at your pace.

Pros and Cons of the Udacity’s Programming for Data Science with Python Nanodegree:

So after discussing all the prerequisites, costs, duration, and syllabus of the Udacity Programming for Data Science with Python Nanodegree Program.

Now, let’s discuss some of the Pros and Cons of Udacity Programming for Data Science with Python Nanodegree Program.

Pros:

Data Science is quite a big field, different roles are available on the basis of various technologies and skills, and that’s the reason why it becomes one of the best career choices for any of the students or even professionals.

This Udacity Programming for Data Science with Python Nanodegree Program will provide you with everything you need to clear your basics in the field of Data Science.

This Nanodegree program is for beginners who want to explore Data Science and eventually select it as their career path. 

As usual, you will perform various practical stuff in this Nanodegree Program. This Nanodegree Program has three projects which cover all the concepts and topics taught in the courses.

Investigating a Database while working with PostgreSQL, exploring US bikeshare data, and posting your works and projects on GITHUB.

These are the projects of the Nanodegree Program which provide practical knowledge enough for any students and professionals who want to explore and get into the world of Data Science.

Top-class technical mentor support throughout the program. They always motivate you and help you to stay on your track while pursuing the course.

With Udacity there is always personalized learning at your pace and achieving personal goals with the help of their flexible learning program.

Studying with Udacity will always give you the advantages of a Personal career coach and services to help you out in interview preparation, building a resume, and online professional profile to boost your career.

The Course has been rated 4.7 stars out of 5 by most of the learners and graduates enrolled in the program.

Financial support is available worldwide in this challenging time of Pandemic for you to stay sharp and on track with the Nanodegree program.

This Udacity Programming for Data Science with Python Nanodegree program provides everything a beginner requires to become successful in the field of Data Science.

Jobs and their value in the field of Data Science are expected to double in the near future. This would be a golden opportunity for Data Science enthusiasts to build a progressive career in the field of Data Science.

Cons:

This Udacity Programming for Data Science with Python Nanodegree Program is for beginners. Topics such as SQL and Python Programming will be taught to you from beginner to intermediate level.

So if you already have Programming and Database knowledge along with version control systems such as GIT, then you may find this course boring. But Still working on the project will revise all your concepts and topics required for Data Science.

Udacity Programming for Data Science with Python Nanodegree Certificate

You will receive a similar Udacity Programming for Data Science with Python Nanodegree certification upon graduation and completion of the complete program.

Well, you should know that this certificate is not accredited by any university but it’s definitely a perfect way to show potential recruiters your qualification and skills. 

You should definitely add it to your LinkedIn or Github profile to highlight yourself as a Data Science expert. You can easily access your certificate through your Udacity account.

The Advance features you get with Udacity

Udacity is popular for its valuable and updated courses which have helped thousands of students, learners, and professionals to improve their skills and land a better job.

Apart from the courses and lessons in the program, they offer some extra services which makes this Programming for Data Science with Python Nanodegree program so special. Let’s have a look at some of their services.

 1. Mentorship

They have a world-class mentorship which is one of the best parts of the Udacity programs. Mentors guide you throughout the entire program. 

They will try to answer your every query and doubts which you might face in the program. Also, they will be responsible for reviewing your projects and providing feedback.

They already know how challenging some of the typical concepts can be, so they will always be in your corner to boost your confidence and motivate you.

Very professional and personal mentorship was provided. Most of the mentors are working in the industry, so they really know how to prepare you.

2.Community and discussion forums

Udacity has a nice community feature where you will meet other like-minded peers from your batch and communicate with them.

You can share your ideas, ask a question in a group of students, and build a professional classroom-like environment.

3. Projects and High-Quality content

The quality of the content of any online learning platform is what really matters. It is more important than any other stuff available online. Here in Udacity, you will get high-quality content and project-based learning, the programs are overall project-centric.

You will be working on some realistic and interesting projects, which will definitely help you to gain more practical experience. All of your projects will be reviewed by your mentors who will guide you throughout the program.

You can add your projects and certificates to your Linkedin profile to attract potential employers. The instructors are industry professionals and many of them come from big MNC’s. 

I have got many valuable comments, resource recommendations and code reviews not only specific to the course but generally to the long-term road.

4. Graduation certificate

Having a certificate from a reputed Massive open online course is always an advantage for you. After the completion of the Udacity Programming for Data Science with Python Nanodegree program, you will receive a decent graduation certification from them.

Most of the employers and potential recruiters are aware of the value of the content provided by Udacity and other big online educational platforms.

Instructors for Udacity Programming for Data Science with Python Nanodegree

1. Josh Bernhard (Data Scientist at NerdWallet)

Josh has been sharing his passion for data for nearly a decade at all levels of the university, and as Lead Data Science Instructor at Galvanize. He’s used data science for work ranging from cancer research to process automation.

2. Derek Steer (CEO at MODE)

Derek is the CEO of Mode Analytics. He developed an analytical foundation at Facebook and Yammer and is passionate about sharing it with future analysts. He authored SQL School and is a member of Insight Data Science.

3. Juno Lee (Curriculum Lead at Udacity)

Juno is the curriculum lead for the School of Data Science. She has been sharing her passion for data and teaching building several courses at Udacity. As a data scientist, she built recommendation engines, computer vision and NLP models, and tools to analyze user behavior.

4. Richard Kalehoff (Instructor)

Richard is a Course Developer with a passion for teaching. He has a degree in computer science and first worked for a nonprofit doing everything from front-end web development to backend programming to database and server management.

5. Karl Krueger (Command Line Instructor)

Karl is a Course Developer at Udacity Before joining Udacity, he was a site reliability engineer (SRE) at Google for eight years.

Check this out -> Udacity Introduction to Python Review: Is it worth it?

Reviews from graduates of Udacity’s Programming for Data Science with Python Nanodegree

“I really like it and think things are very well explained. The exercises on each chapter make you identify clearly the things you got clearly and the ones you didn’t, making you revise and understand everything. – Isabel C.

“The program seems to be going very well thus far. . Additional positive notes are that the technical mentor responded to my question very quickly, and my SQL project was reviewed very quickly as well. The search feature also seems quite helpful. Thanks!” – Dean A.

Toheeb Ayoola Abolade

Data Analyst at Redot Agency

★★★★★

About a month ago, I took the first huge step to transitioning into a new career, Data Science, by enrolling in Udacity’s Nanodegree Program. I enjoyed being a part of the Nanodegree Blueprint. It was a great experience, and I got the chance to sharpen my mind and pick up new skills along the way. Thanks to instructors who twisted and pulled my mind in ways I wouldn’t have considered while encouraging me to find the needed answers.

Here’s a link to my capstone project:
https://lnkd.in/eftyCdN

     -via LinkedIn

Vivek Chavan

React Nanodegree | Cloud Developer Nanodegree | Blockchain Developer Nanodegree at Udacity

★★★★★

This course gave me a great learning curve. I learned how to manipulate large datasets, perform version control, and access modern databases. I got to know about the fundamental programming tools for data professionals: Python, SQL, the Terminal and Git.

David Torres

Data Analyst, Global Logistics Procurement at Johnson Controls

★★★★★

In this course I learned how to extract and manipulate data using SQL and Python through Pandas Dataframes; furthermore, I learned version control with Github.

Today I’m focusing on expanding my Python skills and understanding business perspectives to generate actionable insights.

     -via LinkedIn

Antonio Riccelli

Supply Chain Analyst | Excel, SQL, Python, Tableau

★★★★

I would recommend it to anyone looking to expand their skill set in this direction.

The program is split into three chapters focusing on PostgreSQL, Python (using Numpy and Pandas libraries), and Git/Github, each with a final project.

Had a lot of fun with the Python project, in particular, it was good practice in that it requires the student to write functions that collect the user’s input and use it to filter a DataFrame before showing the required statistics – recommended!

     -via LinkedIn

Conclusion – Is the Udacity Programming for Data Science with Python Nanodegree Worth it?

Data Science is a trending field and has established itself as one of the best career options available in the industry. Data Science is expected to become the most appealing sector in the Information technology industry.

One of the realities of Data Science Jobs is that there are more jobs related to Data Science available than the qualified and eligible professionals suitable for the job.

The reason behind this is the lack of knowledge and skills required for the position related to Data Scientists.

This Nanodegree program will provide you with theoretical as well as practical exposure to various concepts of Data Science.

Working on a realistic project and completing it on your own literally boosts your confidence to face various tech interviews for the role related to Data Science such as Data Scientists, Data Analyst, Data Engineer, Business Intelligence Analyst, and Marketing Analyst.

In this Udacity Programming for Data Science with Python Nanodegree review, you will get to know about the Syllabus, prerequisites, Pros, and cons of this Program offered by Udacity.

You should also know that there is always trust with Udacity. Udacity is backed by most of the top companies in the industry.

After learning the valuable skills from this Nanodegree program you can apply them to various applications such as personalized healthcare recommendations, Stamping out Tax Fraud, Automating digital ad placement, identifying and predicting disease, etc.

Overall this Udacity Programming for Data Science with Python Nanodegree Program is up to the mark and is best for beginners who want to become successful in the field of Data Science or crack the interview for the role related to it. This job role is in demand, respectful, and future-proof.

At last, We say Yes to this Udacity Programming for Data Science with Python Nanodegree program, however, it’s all up to you, how talented you are and what you’re gonna do to extract out the best possible outcome from this Nanodegree Program.

FAQ’s of Udacity Programming for Data Science in Python Nanodegree

1. Why should I enroll?

As we already said, the demand for Data Science professionals is high and the supply of quality Data Science Professionals is less, so you should take advantage of this situation if you are a Data Science enthusiast.

Remember this condition will not sustain forever as Data Science is definitely going to be a more competitive field in the upcoming future.

So, you should enroll in this and the related Nanodegree program and try to build a successful career in the field of Data Science.

2. What jobs will this program prepare me for?

This Udacity Programming for Data Science with Python Nanodegree Program is designed to develop your basic Data Science skills such as Python Programming, Structured Query Language, and version control. 

This program does not prepare you for any specific job but it definitely expands your area of knowledge and skills specifically in the Data Science domain.

You can apply these skills to various applications such as personalized healthcare recommendations, Stamping out Tax Fraud, Automating digital ad placement, identifying and predicting disease, or use it as per your requirements.

3. How do I know if this program is right for me?

This Udacity Programming for Data Science with Python Nanodegree Program offers an ideal path into the world of Data Science.

This Nanodegree Program will quickly teach you the foundational data science programming tools such as Python, SQL, Git.

No prior knowledge is required for this Nanodegree program as most of the things will be taught from basics. This Nanodegree program has various realistic projects which will help you a lot in gaining theoretical as well as practical knowledge.