Transcripts
1. Class Introduction: Hi. In this course, you will
learn how you can start your freelance career as a
beginner Python developer. If you have no idea
regarding fight than having not hard math and you are
confused in what to learn, how to learn, and
from there too large, then you have landed
on the right place. Because in this class, you will learn why
you as a beginner, need to start your career as a freelancer and why you
should start it with Python. I forgetting answers of
these crucial questions, you will dive into the
practical part where you will learn about your
Python draws met in detail. In that part, you will get answers regarding you
are lending patterns. Finally, you will learn which
platform you should juice. And I will share some tips based on my personal
experiences. So if you are interested, then click on the next lecture and I'll see you there. Bye bye.
2. Why you should start with Freelancing?: In the recent years, Lansing has become more
popular than ever. Benefits and freedom
of being your own boss insisted 1 third of the
pupil to pursue it. You can consider freelancing
as a side hustle, a part-time job, or
a full-time job. Many who consider venturing
into freelancing vary. If it's a wise choice
while it may take both die and hardware
to get started. But becoming a
successful freelancer is achievable and comes
with many benefits, and they will discuss
three of them below. One of the biggest
advantage of working independently as a freelancer is gaining the
freedom of choice. And it's up to you which
new clients you tack on, what your hourly rate is
and what are your work. Freelancing is a getter
that to opportunities. As you can work with different clients on
different projects, different environment,
it can help you establish new
relationships, new friends. And this opens the
doors off. For sure. Lansing means you deck on various projects from
multiple clients. Each project brings
its own challenges to the table and provides you an opportunity to
expand your skill set. Surprisingly, you can choose how you want to enhance
your skill set.
3. Why Python?: There are a couple of
reasons why you should start your career with Python, but we will discuss
three of them. Initially. Then you jump into field
of computer science. You don't have that
much clearer image regarding your part, your career, and you are
specializations subjects. At that time, you
need a Swiss knife, which fits almost
in every field. And Python is really
a Swiss knife. From web and software
development to data analysis, from artificial intelligence
to data engineering, from automation to
FBI development. It fits in almost every field. Secondly, by ten is a
beginner friendly language. It is dynamically typed, which saves developers time by automatically understanding
the datatypes. It has huge community and allows beginner to find the solutions
of their problems easily. Finally, huge number
of libraries and frameworks have been
developed for pattern, which reduces development time. Yes, Python is backed by tech
giants, Netflix, spotify, Google, YouTube,
Facebook, Amazon, and so many other tech
companies use fightin. Keeping all of the
above reasons in mind, one should start IT
career that fight them.
4. Python Roadmap: Have you ever heard about
burrito principle states that roughly 80% of outcomes
from 20% of causes. Now you have hard, so many people that you need to spend so many vehicles
in learning Python. But it's not true because
initially you need to know all the dos things
which you'll use 80% in everyday development. So let's talk about
them one-by-one. First of all, when you jump in the field of computer
programming, you need to know about
different types of languages. What is an interpreted language and what makes it
different from it, from a compiled one. Then what our IDE, or integrated development
environments, after these basic prerequisites, jump straight into coding. Learn about variables
and how to declare them. What are data types and what is the difference between
an integer floor, complex and Boolean data type. Learn deeply about
collection data types, which includes released
Drupal set and string, and learn their use cases. Typecasting is a very
unique feature of Python and helps
in many scenarios. So keep it in your
list as the make hundreds of decisions
in everyday. Similarly, decision-making is very crucial in programming, which can be implemented
through conditions. Learn when to use, if, if else or if Alice. After conditional
programming, learn about loops and
what's next for loop, different from a vine. Excellent. You had completed
step number one. Step number two, get your hands dirty with functional
programming in Python. How to declare a
function difference between method and function, passing arguments
or parameters to the function and vorticity
purpose or for return keyword. You also need to have a clear understanding
of lambda function, recursion, decorators,
local and global variables. In step them but three, dive into our object
oriented programming. There you learn about
classes and objects. Why init function is
called constructor. Difference between gloss
and instance variables. What makes static instance and loss method different
from one another? Learn about inheritance,
polymorphism, encapsulation, duck
typing X sector. The final step, learn about
common Python libraries, how to install and import them. Learn about error handling and file handling.
I prefer London. All of these about
topics which will detect did during 25 R's, you have a strong
best of Python. Now, it's time to
practice questions. There are bunch of websites
out there to practice pattern spent around or
vague in practicing section. And I'll see you in
the next lecture.
5. Let's be Specific: After learning Python, now, if you are thinking that you are ready to jump into freelancing, then you are wrong. No one has any interest
in your Python skills. Everyone on freelance
marketplace is problem-solvers. Now, it's time for
you to learn about problems of specific said and try to solve
them with Python. Here is the list of
different fields where you can use patents for
problems solving. These are denying major fields. There. You can apply your Python skills that you can solve the
problems only with Python. Rather, you need to learn some
specific Python libraries and frameworks for each field
in order to solve problems. In the next lectures, there talk about them in detail.
6. Web Technologies: If you are interested in technologies and want
to solve the problems, then buttons suits you the best. You can test your
pattern scales in that scrapping lab automation,
back-end development. Let's discuss them one-by-one. That's scrapping is the
process of extracting data from different types
of websites using boards. If you want to develop
these boards in Python, you need to learn. Python Requests Library, Beautiful Soup library,
and scrappy framework. Let's see how much time you need to spend on each of them. First of all, requests, library, even deck, hardly two
hours of learning. Beautiful Soup. Four requires six to
eight hours of learning. Finally, scrapie
is a framework and required ten to 15
hours of learning. You are required to spend
two to three days in order to become a
Python web scraper. The process of performing
predefined actions, tasks, and processes on the web
browser Thru Bars is called that automation
is well-known for automating tasks and you can automate that best does using Selenium framework
along with requests and BeautifulSoup for
at least than ours, are required to learn
selenium completely. If you have little
bit of HTML, CSS, and JavaScript knowledge than back-end development
matches you. The help of Flask and
Django framework. You can develop the backend
of that site in Python, but you need to do hard
work in the beginning. Plus is a small
framework and you can learn it in 1.5 week. While Django requires at
least one month of learning. After learning them, do 23 projects in order to
nourish your skeleton.
7. Development in Python: Although python is an
interpreted language, but it's still
allow us to develop powerful MPI applications
and even games. Now, let's discuss
which libraries and frameworks you need to
learn in each category. Application programming
interface, or API, is a communication between
two computer programs. Fbi development in Python, it's possible that both
floss and fast API, but FastAPI is completely optimized for API
development in Python. Along with this, you
need to learn about databases like Postgres, SQLite. Along with some
experience in SQL, fast FBI can be learned
and add to ten hours. Lot SQL requires
two to four Rs and Postgres requires four to
six hours of learning. I recommend to you that after
learning API development, Mac, one or two APIs, deploy them on rapid FBI. There you can turn your APIs
into our revenue stream as valid by the is also a good choice for app
development because of GAVI, D converter and phi q t. These are the three
separate frameworks that allows you to develop
applications in Python. All of them have
their own advantages. You can easily learn TV
in eight to ten hours, while teak in turn requires four to five hours
of learning by Judy is a big
framework and requires 15 to 17 hours of learning. Finally, game development
in Python was made possible with the
help of Pi game learning, design texts, function and method of pi gamma
is quite easy. But the most challenging part in game development is
the creation of logic. You can learn pi get in 15 to 17 hours
after learning Mac, at least two games and
applaud them on GitHub. And then link to get help with the freelance marketplace that will act as your portfolio.
8. Artificial Intelligence in Python: Relationship between Python and artificial intelligence is
same as that of water and ice. You can't pursue in artificial intelligence
without pattern, the market is experiencing
robust growth. Status reports or global
market size of 32700000002021, which will expand to 190. Why 61 billion by
2025 only in US. If you want to pursue your
career as an AI engineer. Start from data analysis, machine learning, and
natural language processing. Data analysis is the process of extracting information
and insights from data. In Python, NumPy and Matplotlib really helps
in data analysis. Numpy is a numeric library which allow us to play with
arrays in Python. Usually Dec. seventh to
add hours of learning, bond does allow us to claim, manipulate, and extract data
from different types of files like CSV, exit, etcetera. It requires 15 to 20
hours of learning. Matplotlib is a data visualization
library which allows us to display data in form
of graphs and charts. There are some
other alternatives, like C-H bond and Plotly, but not a lot left, is a well-known and easy to
learn library, which deck? To seven hours of learning. After learning these libraries, you need to learn some basic
mathematics and statistics, which required 20 to
30 hours of study. Mit defines machine
learning as the capability of a machine to imitate
intelligent human behavior. Machine-learning systems can be descriptive, predictive,
and prescriptive. This can be achieved using different statistical techniques and algorithms and Python, Scikit-learn or
Escalade, TensorFlow and PyTorch are commonly used libraries for
machine learning. But as a beginner, what one you should choose
based on some statistics. Every machine learning beginner should start from SKLearn, which is more general
purpose and easy to learn machine learning
library after it, tensorflow is the
neck, which is again, easy to learn, Google
powered ML library. But it is used commonly for deep learning and
neural networks. Both of them require one
to two months of learning. Along with it, you need to know some mathematics and statistics. Natural language
processing, or NLP, is the computer's ability to
understand human languages. Python, NLTK, Bessie,
and phos decks. I've commonly used for training natural language
processing models. Crushed or fall, start
lending from speci that jumped to NLTK and
then to foster text. All of them are so much easy that you can learn
them. They did number.
9. Best Platform: Great job. Now you are ready to jump
into freelance market. But should you start
from Fiverr app for or any other than
stone experience? Initially, you should
start from fiber. There are two main reasons. Firstly, it is designed for both beginners
and professionals. So you can polish your patterns skills by
working on small projects, which will let you bent
visible reputation. Secondly, buyers
will come to you. You don't have to bid
to get customers. We don't have to spend all day bidding on potential projects. Just sit back and that foreign notification
email to arrive once you have
etiquette experienced than you can switch to
other freelance pellet. Bye-bye.
10. Class Project: After attending the class. Now, your task is to make a pattern roadmap according
to your interest. Also mentioned the
timestamps and share as your class project in
order to help others. Hope you have enjoyed this class and I'll see you later. Bye-bye.
Umair Ahmed, Computer Enthusiast
