As the world has made its foray into the era of big data in the last few decades, the requirement for better and more efficient data storage has become a significant challenge. The main focus and concern of businesses employing big data has been on building up frameworks capable of storing a huge amount of data, thereby creating Hadoop and other frameworks for the purpose of storing massive amount of data. Thereafter, there’s a shift in focus towards processing the stored data, and this’s where data science comes into the picture, meant for processing and analyzing data. However, companies in today’s time hire data scientists and professionals capable of turning and transforming data into meaningful resources for benefits and prospects of companies and business establishments.
Introduction to Data Science
Data Science imparted at Python Data Science Courses, is all about finding and exploring data in real world and making use of that knowledge for solving business problems. Some instances of data science taught at Python Data Science Training institutes include:
- Customer Prediction for likelihood of customers purchasing products.
- Service planning for predicting the number of customers visiting, say, restaurants and plan their food inventory accordingly.
Fundamental Skillsets Required for Data Science:
- Programming Language like Python, in other words, Data Science with Python, or R programming language
- Machine Learning Skills
- Mathematics
- Data Visualization
- Statistics
- Big Data
- Data Wrangling
Programming Language for Data Science:
Python is the most popular data science programming language taught at Python Data Science Courses taught at Python Data Science Training institutes. It’s popular owing to the following reasons:
- An accessible and highly interpretable language, an open-source software that anyone can use.
- Errors in Python Coding are easy-to-understand.
- Writing Python Programming is similar to writing sentences in English, also facilitates in debugging and exception handling.
- Scikit-Learn, NumPy, Pandas, and Matplotlib are instances of Python libraries used for solving data science and machine learning problems.
Why Python Language?
When it comes to data science, we require some sort of programming language or tool like Python taught at Python classes in Pune or elsewhere. Python as a programming language, in other words, Python Programming, or in simple terms, Python Language has assumed popularity of late, and has been employed in data science, IoT, AI, and other technologies. In fact, Python is used as a programming language for data science as it constitutes expensive tools from mathematical or statistical perspective. This explains why data scientists trained in Data Science with Python course, the world over, use Python.
There’re several other reasons why Python is one of the most sought-after languages for data science, including:
- Speed-Faster compared to other programming languages.
- Availability-Significant number of packages available, which can be reused.
- Design Goal-Syntax roles in Python being intuitive and easy-to-understand.
- Choice of Libraries-Massive libraries like NumPy, Pandas and SciPy easily accessible in tutorials form.
- Visualization & Graphics providing many options.
- Large & active community of Python developers.
- Portable & cross-platform language running on varied platforms like Windows, macOS, Linux, Android.
- Object-oriented
- Dynamic typing
- Garbage collection managing memory allocation and deallocation.
Python for Data Analysis| Python Libraries for Data Analysis:
Python Programming is a simple programming language to learn, with basic stuff that one can do with it such as adding, printing statements, and so on. However, if one wants to perform or do Python for Data Analysis, then one requires to import specific libraries like:
- Pandas-Used for structured data operations
- NumPy-A powerful library helping you create n-dimensional arrays
- SciPy-Provides scientific capabilities such as linear algebra & Fourier transform
- Matplotlib, Seaborn, Bokeh & Plotly-Primarily used for data visualization purposes
- Scikit-learn-Used for carrying out machine learning activities
- Networks & I graph
- TensorFlow
- BeautifulSoup
- OS
Learn Python, master the fundamentals of Python Programming, say, Python for Beginners, and gain in-depth, beneficial knowledge pertaining to data analytics, data visualization, Exploratory Data Analysis (EDA), Statistics, machine learning & deep learning. Goes without saying, there’s Python for Everybody!
Best Data Science With Python Courses for Beginners With No Experience:
- IBM Data Science Professional Certificate (Coursera Python)-This’s a great course for beginners aspiring to learn the basics of data science. It encompasses topics like Python programming, data cleaning, data analysis, and machine learning. This Python Data Science Training is imparted by experts from IBM including hands-on projects for helping you learn the material.
- Applied Data Science with Python (University of Michigan)-This course is designed for teaching you the essential skillsets required to become a successful data scientist, covering topics like Python programming, data analysis, machine learning and data visualization. This Python for Beginners course is taught by experts from University of Michigan including hands-on projects for helping you learn the material.
- Master Python for Data Science (LinkedIn Learning)-This course is designed to help you learn the Python Programming language, in other words, Python Language specifically for data science. It covers topics like data structures, algorithms, and libraries such as NumPy, Pandas, and Matplotlib. The course is taught by experts from LinkedIn Learning and includes hands-on projects.
- Data Scientist with Python (DataCamp)-This course is designed to help you learn the essential skillsets required to be a data scientist, covering topics like Python Programming, Python for Data Analysis, machine learning and data visualization. The course is imparted by experts from DataCamp including hands-on projects.
- Complete Data Science Package (GeeksforGeeks)-This course is designed for helping you learn the essential skills needed to be a data scientist. It covers topics such as Python Programming, data analysis, machine learning and data visualization. The course is taught by experts from GeeksforGeeks and includes hands-on projects.
Other Courses of Data Science with Python for Beginners (Free Options):
- 365 Data Science-website for Python for Beginners offers a comprehensive data science career track with several free courses and learning resources.
- Google Data Science Specialization offered via Coursera Python, provides solid foundation in data science concepts and tools using Python.
- HarvardX Data Science: R Programming & Data Analysis-free course from Harvard University introduces basic data science concepts and teaches R programming language.
- Microsoft Learn: Data Science Fundamentals-platform offering free learning path covering data science fundamentals including Python basics, Python for Data Analysis, and visualization.
- Kaggle Learn-platform offering a variety of free courses and tutorials on data science topics, including machine learning, deep learning and data analysis.
Paid Options for Python Programming for Beginners:
- Springboard Data Science Bootcamp-provides a comprehensive learning experience, covering essential data science skills, preparing you for a career change.
- Udacity Data Scientist Nanodegree-one amongst the Best Way to Learn Python is to learn this program focusing on hands-on learning, with projects for building up your portfolio and preparing you for real-world data science applications.
- Dataquest-offer interactive courses and learning paths for data science, enabling you to learn at your own pace and tackle projects in varied domains.
- Pluralsight Data Science Path-provides access to a curated selection of courses covering a wide array of data science topics, along with hands-on exercises and assessments.
- edX Data Science Courses-offers various data science courses from top-notch universities and institutions, including MIT, Harvard, and IBM.
Learn Data Science with Python via Additional Resources:
- Data Science for Everyone by Foster Provost & Tom Fawcett-This book provides a gentle introduction to data science concepts and tools for beginners.
- Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow by Aurelien Geron-This book provides a practical guide to machine learning using Python libraries.
- Python for Data Science by Wes McKinney-This book teaches Python Programming language specifically for data science applications.
- Data Science Podcasts-discusses data science topics and careers like Data Skeptic, lex Fridman Podcast, and TWIML AI Podcast.
- Data Science Communities-Online communities such as Kaggle, Reddit’s r/data science, and Data Science Central offer opportunities for connecting with other aspiring learners and professionals.
Python Programming for Data Science:
- Fundamentals
- Data Types
- Variables & Operators
- Control Flow
- Functions
- Essential Libraries
- NumPy
- Pandas
- Matplotlib
- Scikit-learn
- Data Acquisition & Wrangling
- Import data
- Data cleaning
- Data transformation
- Data Analysis & Exploration
- Descriptive statistics
- Data filtering & sorting
- Correlation analysis
- Exploratory visualization
- Machine Learning
- Understand key concepts
- Implement common machine learning algorithms
- Build & train models
- Evaluate model performance
Key Aspects of Python Coding for Data Science & Data Analytics:
- Data types
- Operators & expressions
- Control flow
- Functions
- Importing data
- Data cleaning
- Data manipulation
- Data transformation
- Descriptive statistics
- Data visualization
- Correlation analysis
- Understand key concepts
- Implement machine learning algorithms
- Train & evaluate models
- Hyperparameter tuning
- Data exploration & analysis
- Data storytelling
- Model deployment
Python Developer: Responsibilities, Skills, & Career Path
- Responsibilities
- Design & development
- Testing & debugging
- Deployment & maintenance
- Documentation
- Collaboration
- Learning & knowledge sharing
- Skills
- Strong understanding of Python Language
- Experience with Python libraries
- Software development principles
- Problem-solving skills
- Communication & collaboration skills
- Ability to learn & adapt
- Career Path
- Junior Python Developer
- Mid-Level Python Developer
- Senior Python Developer
- Python Architect
- Data Scientist
- Web Developer
Coursera Python Course for Beginners:
- Python for Data Science, AI & Development
- Python Programming Fundamentals
- Python for Everybody
- Get Started with Python
- Programming for Everybody
- Google IT Automation with Python
- Programming in Python
- Create Your First Python Program From UST
- Introduction to Scripting in Python
- Introduction to Programming with Python & Java
- Python for Beginners: Variables & Strings
Coursera Python for Everybody Specialization:
- Programming for Everybody (Getting Started with Python)
- Python Data Structures
- Using Python to Access Web Data
- Using Databases with Python
- Capstone: Retrieving, Processing, & Visualizing Data with Python
Duration to Learn Python on Coursera:
Time to completion tends to vary based on one’s schedule and experience level, but most learners are able to complete the Specialization in about 8 months.
Best Way to Learn Python:
The best way is by using it. Working on real projects gives you the opportunity to apply the concepts you’ve learned and gain hands-on experience. Start with simple projects that reinforce the basics, and gradually take on more complex ones as your skills improve. However, besides Coursera, Learn Python with data science at Scoopen School of Program Engineering, located at Dhankawadi, Pune India, imparting Python Data Science Courses, Database Power BI, SQL PLSQL, Business Analyst, SAP SD MM HANA, AWS Azure DevOps, Micro.Net, Angular JS, Java Course, Soft Testing, providing biggest competitive Cloud Analytics, and Automation platform in Pune. Established in 2011, Scoopen School of Program Engineering has earned topmost position amongst a plethora of Computer Training Institutes, equipped with best-in-class professional, experienced mentors having sound technical knowledge in structures and project management, imparting easy-to-understand style presentation. Scoopen School is bestowed with accolade of Excellence Award Winner in 2016, 2017 & 2018 in Multiple technologies by PROGVALTON TECH for its outstanding proficiency and excellence paving way for exponential growth.