7 answers
Aaru
Student
Mumbai, Maharashtra, India
5
Questions
Asked
1479 views
How should I start my journey to learn coding and programming so that I can pursue a career in data science?
i am a complete beginner to coding and i want to pursue a career in data science. i started watching tutorials on yt but i was unable to understand anything. i figured i should start with python however it is easier said than done. what can i do??
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7 answers
Doc Frick
Career Coach and Mentor
1590
Answers
California, CA
Updated
Doc’s Answer
If you really want to learn how to code Aaru, you need to do more than just watch a video — you need to put the information you’re learning into action. I suggest, you should actually start coding as you’re learning. That way, you put the information to use immediately. When you learn by doing, the information will be more likely to stick with you. It might seem old school, but if you really want to succeed in computer programming, especially if you are seeking a coding career, learning to code by hand is one of the most important skills you can learn. First of all, it will make you a better coder because you’ll have to be more intentional — you won’t be able to run your code halfway through to see if it works. This results in an increased level of precision. But learning to code by hand doesn’t just improve your skills; it can also help you get a job and jumpstart your coding career. Employers looking to hire computer programmers often require applicants to take a coding test that involves coding by hand. Therefore, it’s essential that you acquire this skill.
CODING PROGRAMS FOR BEGINNERS
• PYTHON — Python is a high-level programming language that’s more for general purposes. It’s one of the most popular programming languages globally and can be used to build websites and software, automate tasks, and conduct data analysis. This coding language is easy to use for both programmers and non-programmers. It uses a simple syntax which mimics natural language, making it easier to read and understand than other code. It’s also open source and has a large, active community who contribute to its pool of libraries, offering a great resource to new learners.
• C — One of the longest-standing programming languages, C is a general-purpose language that’s very popular and flexible in its use. It is often used to write applications and Operating Systems, and can offer a great base of knowledge for other coding languages. Unlike other code with upwards of 50-60+ keywords, C only uses 32 keywords, making it a simple-syntax language. Since it has been around for so long, any problem you want to solve C will also have a solution online, making it easy to cross-check and compare your work.
• JAVA —Java is another long-standing coding language; it has been around since 1995. One of the first and most famous coding languages in the world, Java uses classes and objects to execute commands, and is based on C. This language has many uses such as apps, servers, and games. Java is well-structured and object-oriented, providing a solid framework that makes it an easy-to-learn coding language for beginners. As such a wide-spread programming language, Java has lots of resources for new learners.
CODING PROGRAMS FOR BEGINNERS
• PYTHON — Python is a high-level programming language that’s more for general purposes. It’s one of the most popular programming languages globally and can be used to build websites and software, automate tasks, and conduct data analysis. This coding language is easy to use for both programmers and non-programmers. It uses a simple syntax which mimics natural language, making it easier to read and understand than other code. It’s also open source and has a large, active community who contribute to its pool of libraries, offering a great resource to new learners.
• C — One of the longest-standing programming languages, C is a general-purpose language that’s very popular and flexible in its use. It is often used to write applications and Operating Systems, and can offer a great base of knowledge for other coding languages. Unlike other code with upwards of 50-60+ keywords, C only uses 32 keywords, making it a simple-syntax language. Since it has been around for so long, any problem you want to solve C will also have a solution online, making it easy to cross-check and compare your work.
• JAVA —Java is another long-standing coding language; it has been around since 1995. One of the first and most famous coding languages in the world, Java uses classes and objects to execute commands, and is based on C. This language has many uses such as apps, servers, and games. Java is well-structured and object-oriented, providing a solid framework that makes it an easy-to-learn coding language for beginners. As such a wide-spread programming language, Java has lots of resources for new learners.
Thank you so much for the advice.
Aaru
Dennis Taylor
Self-employed
83
Answers
Columbus, Indiana
Updated
Dennis’s Answer
Hello Aaru,
THe answers posted before mine are great. You can learn quite a lot about programming and programming language from them.
I am not trained in Computer science per se, so I will take a different approach: I won't recommend a language or tutorial. I offer this instead: "data" and "statistics" offer us a way to understand our world. In most cases, we use some kind of mathematical model to help us do that. But, never forget that you are dealing with people, their lives, customs, mores and so on.
Second; using a computer system to do the data collection and analysis is just using a TOOL to help you do your job more accurately, consistently and (maybe) faster. But, YOU are still the one doing the analysis and conveying the result to others.
Thirdly; programming (or programming languages) are just a means for you to communicate your (mathematical and logical) ideas to a machine that can do nothing more than add, subtract and compare digits. Most processors now have a multiply/divide function, but it has limitations depending on the "type" of data you give it. Also , in the code examples by Rajan, you see that more complex math uses arrays and matrices. Again, these are tools you will have to learn to employ at the right juncture. These higher-level tools are usually provided in a library of functions for the specific programming language you will be using. In this respect, learning a given programming language is like learning a dialect of your native language. For me, I think (written) "music" is an excellent example of programming: a symphony written 400 years ago can be performed today by a group of musicians who do not have any speaking language in common. The performance will still sound pretty much the way the composer intended it!
Most computers have a processor with a specific (machine) instruction set, and some associated programming language(s), that help you program at a higher language level that (ideally) speeds up the coding and debugging process. Spend some time learning about this as well.
I wish you well in this endeavor, Aaru!
THe answers posted before mine are great. You can learn quite a lot about programming and programming language from them.
I am not trained in Computer science per se, so I will take a different approach: I won't recommend a language or tutorial. I offer this instead: "data" and "statistics" offer us a way to understand our world. In most cases, we use some kind of mathematical model to help us do that. But, never forget that you are dealing with people, their lives, customs, mores and so on.
Second; using a computer system to do the data collection and analysis is just using a TOOL to help you do your job more accurately, consistently and (maybe) faster. But, YOU are still the one doing the analysis and conveying the result to others.
Thirdly; programming (or programming languages) are just a means for you to communicate your (mathematical and logical) ideas to a machine that can do nothing more than add, subtract and compare digits. Most processors now have a multiply/divide function, but it has limitations depending on the "type" of data you give it. Also , in the code examples by Rajan, you see that more complex math uses arrays and matrices. Again, these are tools you will have to learn to employ at the right juncture. These higher-level tools are usually provided in a library of functions for the specific programming language you will be using. In this respect, learning a given programming language is like learning a dialect of your native language. For me, I think (written) "music" is an excellent example of programming: a symphony written 400 years ago can be performed today by a group of musicians who do not have any speaking language in common. The performance will still sound pretty much the way the composer intended it!
Most computers have a processor with a specific (machine) instruction set, and some associated programming language(s), that help you program at a higher language level that (ideally) speeds up the coding and debugging process. Spend some time learning about this as well.
I wish you well in this endeavor, Aaru!
Rajan Kapoor
1
Answer
Alwar, Rajasthan, India
Updated
Rajan’s Answer
To get started, you can go to https://www.programiz.com/python-programming/online-compiler/ right now and try out these examples step by step :
## Step 1: Basic print command
print("Hello World!")
Step 2: Declaring variables, assigning values and using if statement:
var = 1
if var == 1:
print("Var is 1")
Step 3: Using else:
if var == 2:
print("Var is 2")
else:
print("Var is not 2")
Step 4: Using switch:
match var:
case 1:
print("Var is 1")
case 2:
print("Var is 2")
case _:
print("Var is neither 1 nor 2")
Step 5: Using print with variables:
print(f'var + 1 is : {var+1}')
## Step 6: Using for loop:
for var in range(5):
print(f'Value of var is {var}')
Step7: Using arrays, len(), range(), and for loop
var_array = [1, 5, 10, 11, 15, 20]
print(f'Length of var_array is {len(var_array)}')
for iterator in range(len(var_array)):
print(f'Value of iterator is {iterator}, value of item at iterator is {var_array[iterator]}')
## Step 8: Repeat step 7 with string array below
string_array = ['One','Five','Ten','Eleven','Fifteeen','Twenty']
Step 9: Declaring dictionary and different ways to print keys and values:
string_dict = {1:'One',5:'Five',10:'Ten',11:'Eleven',15:'Fifteeen',20:'Twenty'}
print(f'The keys in string_dict are {string_dict.keys()}')
print(f'The values in string_dict are {string_dict.values()}')
for iterator in range(len(var_array)):
print(f'Value of iterator is {iterator}, value of **string_dict** item at iterator is {string_dict[var_array[iterator]]}')
for key in string_dict.keys():
print(f'Value of key is {key}, and the value corresponding to the key is {string_dict[key]}')
for key, value in string_dict.items():
print(key, ":", value)
## Step 1: Basic print command
print("Hello World!")
Step 2: Declaring variables, assigning values and using if statement:
var = 1
if var == 1:
print("Var is 1")
Step 3: Using else:
if var == 2:
print("Var is 2")
else:
print("Var is not 2")
Step 4: Using switch:
match var:
case 1:
print("Var is 1")
case 2:
print("Var is 2")
case _:
print("Var is neither 1 nor 2")
Step 5: Using print with variables:
print(f'var + 1 is : {var+1}')
## Step 6: Using for loop:
for var in range(5):
print(f'Value of var is {var}')
Step7: Using arrays, len(), range(), and for loop
var_array = [1, 5, 10, 11, 15, 20]
print(f'Length of var_array is {len(var_array)}')
for iterator in range(len(var_array)):
print(f'Value of iterator is {iterator}, value of item at iterator is {var_array[iterator]}')
## Step 8: Repeat step 7 with string array below
string_array = ['One','Five','Ten','Eleven','Fifteeen','Twenty']
Step 9: Declaring dictionary and different ways to print keys and values:
string_dict = {1:'One',5:'Five',10:'Ten',11:'Eleven',15:'Fifteeen',20:'Twenty'}
print(f'The keys in string_dict are {string_dict.keys()}')
print(f'The values in string_dict are {string_dict.values()}')
for iterator in range(len(var_array)):
print(f'Value of iterator is {iterator}, value of **string_dict** item at iterator is {string_dict[var_array[iterator]]}')
for key in string_dict.keys():
print(f'Value of key is {key}, and the value corresponding to the key is {string_dict[key]}')
for key, value in string_dict.items():
print(key, ":", value)
Jadyn Fletcher
Workday Senior Associate
2
Answers
White Plains, Maryland
Updated
Jadyn’s Answer
You did a great job at picking up a preliminary programming language first, Aaru. Python is a great language to start with as it does a great job at teaching you the basics and can smoothly lead into more moderate or difficult programming topics and practices.
When I attempted to learn Data Science, some of the resource I used were Youtube, Udemy (Udemy offers insane discounts that you can buy for $10 for an entire course of practice materials), CodeAcademy, and Coursera (students can usually create a free account and have access to free courses). There are various levels you can start at when finding resources on these sites, so I recommend finding a course/channel that starts at the beginning and leads into intermediate exercises.
Also, I suggest when something is confusing or difficult, don't be afraid to dig further so you can get a better grasp of what's confusing you, find more examples on external resources such as programming forums (like github), or even take a small break and come back to it later.
When you get to a point where you feel that you're confident with what you've learned thus far a good idea is searching on Google for "Python Data Science Projects" and see how far you can get based on what you've learned. This is a huge challenge for you to find gaps in the material you've learned so you can become more polished in it and also have more control in something you create and be able to showcase that to others.
It's important to make practicing and learning a habit but it's also crucial that you have fun with what you're doing, so if you're finding that learning is becoming more of a hassle or stressful, take a break... find a way to make the learning more engaging (by including other interests in your creations)... and maybe take another break (Breaks will do you wonders, I promise :)
I hope this advice helps, and whether you’re starting college or finishing up your studies, Access Your Potential Career Readiness and Digital Skills curricula are available to help you grow and discover what you want for your career. For more information: http://accessyourpotential.pwc.com/.
When I attempted to learn Data Science, some of the resource I used were Youtube, Udemy (Udemy offers insane discounts that you can buy for $10 for an entire course of practice materials), CodeAcademy, and Coursera (students can usually create a free account and have access to free courses). There are various levels you can start at when finding resources on these sites, so I recommend finding a course/channel that starts at the beginning and leads into intermediate exercises.
Also, I suggest when something is confusing or difficult, don't be afraid to dig further so you can get a better grasp of what's confusing you, find more examples on external resources such as programming forums (like github), or even take a small break and come back to it later.
When you get to a point where you feel that you're confident with what you've learned thus far a good idea is searching on Google for "Python Data Science Projects" and see how far you can get based on what you've learned. This is a huge challenge for you to find gaps in the material you've learned so you can become more polished in it and also have more control in something you create and be able to showcase that to others.
It's important to make practicing and learning a habit but it's also crucial that you have fun with what you're doing, so if you're finding that learning is becoming more of a hassle or stressful, take a break... find a way to make the learning more engaging (by including other interests in your creations)... and maybe take another break (Breaks will do you wonders, I promise :)
I hope this advice helps, and whether you’re starting college or finishing up your studies, Access Your Potential Career Readiness and Digital Skills curricula are available to help you grow and discover what you want for your career. For more information: http://accessyourpotential.pwc.com/.
Avirup Ray
Student
39
Answers
New York, New York
Updated
Avirup’s Answer
Python is mostly used in Data Science, so I recommend you learn python first. However, before you delve into watching videos for python programming, I highly recommend watching someone like Abdul Bari who explains algorithms in a simple way. The best way to learn python other than videos is to work on fun small projects. For example, my first python code was a simple program that printed our something about my family members when I typed in their names.
Rebecca Tang
Banking
1816
Answers
Hong Kong
Updated
Rebecca’s Answer
Thank you for your question. I am glad to hear that you have interest on programming and data science.
Below are my suggestions :
1. You can find out the syntax and structure of Python online. There are plenty of resources.
2. Start doing some simple programming yourself. Then, you can do some small projects, e.g. control a toy car, robotic arm, etc. Practise makes perfect!
3. After you familiar with Python, you can learn another programming language in similar way.
4. Explore the entry criteria of data science or computer science in colleges. Work hard on your academic to meet the entry criteria.
Hope this helps! Good Luck!
May Almighty God bless you!
Below are my suggestions :
1. You can find out the syntax and structure of Python online. There are plenty of resources.
2. Start doing some simple programming yourself. Then, you can do some small projects, e.g. control a toy car, robotic arm, etc. Practise makes perfect!
3. After you familiar with Python, you can learn another programming language in similar way.
4. Explore the entry criteria of data science or computer science in colleges. Work hard on your academic to meet the entry criteria.
Hope this helps! Good Luck!
May Almighty God bless you!
Patrick Meyer
Executive - Data Analytics and AI
750
Answers
Naperville, Illinois
Updated
Patrick’s Answer
Aaru, embarking on the path of learning coding and programming to build a career in data science is a bold and fulfilling pursuit. It's okay to feel a bit daunted at the start, especially when you're a beginner trying to navigate through various tutorials and resources. But remember, with the right guidance and a never-give-up attitude, you can indeed master the intricacies and lay a solid foundation in programming.
Python is a fantastic starting point, especially for budding data scientists, thanks to its simplicity, adaptability, and popularity in the field. While it might seem intimidating initially, there are many steps you can take to make the learning process smoother and more enjoyable.
First and foremost, think about signing up for structured online courses or learning programs that are designed specifically for beginners in programming and data science. Websites like Coursera, edX, or Udacity offer thorough courses on Python programming, data analysis, and machine learning, often taught by seasoned instructors who make complex concepts easy to grasp.
In addition, supplementing your coursework with interactive resources like coding exercises, challenges, and projects can greatly boost your understanding and memory of important concepts. Websites like Codecademy, LeetCode, or HackerRank offer practical coding practice and real-world problem-solving experiences, enabling you to put your learning into action.
Also, don't underestimate the power of community support and mentorship to enrich your learning journey. Online forums like Stack Overflow or Reddit's r/learnpython are great places to ask questions, seek guidance, and connect with other learners and seasoned professionals. You might also want to join local coding meetups or data science groups to meet people with similar interests and learn from their experiences.
As you advance in your learning, feel free to explore additional resources like textbooks, academic papers, and online tutorials to deepen your knowledge of Python programming and its use in data science. Consider working on personal projects or contributing to open-source initiatives to further sharpen your skills and demonstrate your expertise to potential employers.
In conclusion, Aaru, always remember that learning programming and data science is a journey that demands commitment, patience, and constant practice. By adopting a structured approach, utilizing a variety of resources, and actively participating in the community, you can effectively tackle the complexities of coding and programming, setting the stage for a thriving career in data science.
Python is a fantastic starting point, especially for budding data scientists, thanks to its simplicity, adaptability, and popularity in the field. While it might seem intimidating initially, there are many steps you can take to make the learning process smoother and more enjoyable.
First and foremost, think about signing up for structured online courses or learning programs that are designed specifically for beginners in programming and data science. Websites like Coursera, edX, or Udacity offer thorough courses on Python programming, data analysis, and machine learning, often taught by seasoned instructors who make complex concepts easy to grasp.
In addition, supplementing your coursework with interactive resources like coding exercises, challenges, and projects can greatly boost your understanding and memory of important concepts. Websites like Codecademy, LeetCode, or HackerRank offer practical coding practice and real-world problem-solving experiences, enabling you to put your learning into action.
Also, don't underestimate the power of community support and mentorship to enrich your learning journey. Online forums like Stack Overflow or Reddit's r/learnpython are great places to ask questions, seek guidance, and connect with other learners and seasoned professionals. You might also want to join local coding meetups or data science groups to meet people with similar interests and learn from their experiences.
As you advance in your learning, feel free to explore additional resources like textbooks, academic papers, and online tutorials to deepen your knowledge of Python programming and its use in data science. Consider working on personal projects or contributing to open-source initiatives to further sharpen your skills and demonstrate your expertise to potential employers.
In conclusion, Aaru, always remember that learning programming and data science is a journey that demands commitment, patience, and constant practice. By adopting a structured approach, utilizing a variety of resources, and actively participating in the community, you can effectively tackle the complexities of coding and programming, setting the stage for a thriving career in data science.