Fast Track Python for Data Science (TTPS4873)

TTPS4873 Python for Data Science Training Course

Fast-Track Your Data Science Mastery with Python!
Over the next several years, there will be a nearly 1000% growth in demand for data scientists and analysis; now is the time to act. Acquiring proficiency in Python is vital for anybody aspiring to work as a data analyst or advance to the data scientist position. Fast Track Python for Data Science (TTPS4873) is a 03-day course where learners master data science and analytics techniques using Python. Using this course, you'll learn the essential concepts of Python programming and gain in-depth, valuable knowledge in data analytics, machine learning, data visualization, web scraping, and natural language processing. 
Enrolling in the Fast Track Python for Data Science (TTPS4873) will provide various benefits to the learners, a few of which are listed below:
•    Mock Interviews and Practice Tests
•    Continuous Skill Improvement
•    Access to Exclusive Content
•    Mobile-Friendly Learning Platform
•    Regular Webinars and Workshops
•    Certification Path Assistance


  152 Ratings

               468 Participants

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Up to 20%

Approved and Quality Ensured Training Material

24*7 Leaner Assistance And Support

Experienced Subject Matter Experts

Instructor-led Online Training

Fast Track Python For Data Science

Data science compiles various data sets to project insights, acquire information, and analyze it to make wise business decisions. Nonetheless, learning some of the finest and most popular computer languages—like Java, C++, R, Python, etc.—is a must for becoming a data scientist. Of them, Python is thought to be the most popular option among data scientists worldwide. In this Fast Track Python for Data Science (TTPS4873), we'll explore the exciting world of Python and its wide-ranging applications in data science. Additionally, we will examine some data science methods with the Python programming language. Above all, this training will provide you with the knowledge and abilities to lead resilient improvement and transformation.
To offer a comprehensive learning experience, Vinsys uses a dynamic combination of teaching techniques. In practical labs, learners will use many robust libraries that simplify data analysis and visualization as they apply their theoretical knowledge to real-world situations. Cooperative group discussions that foster critical thinking and problem-solving abilities are used to enable learners to explore practical solutions while providing a strong theoretical foundation through lectures given by the teacher. To accommodate different learning styles, self-paced learning tools, and online tutorials are easily accessible. Frequent tests and evaluations aid in tracking pupils' development and solidifying their knowledge. After completing the course, students will have access to certification examinations, which will authenticate their knowledge and improve their chances of landing a job in the cutthroat world of Data Science and IT. As we've seen, Python is an increasingly required skill for many data science positions, so enhance your career with this interactive, hands-on course.

Course Curriculum

Target Audience For Fast Track Python For Data Science

Fast Track Python for Data Science Course (TTPS4873)  is for those who want to enhance their Python programming language to make a career in Data Science. 
•    Aspiring Data Scientists
•    Data Analysts
•    Business Analysts
•    Programmers and Developers
•    Statisticians and Mathematicians
•    Researchers and Academics
•    IT Professionals

Fast Track Python For Data Science Prerequisites

Learners taking the Fast Track Python for Data Science (TTPS4873) course should be familiar with the following topics, even if there isn't any compulsion.
•    Basic Computer Skills
•    Python Basics
•    Statistics Fundamentals
•    Some understanding of linear algebra and calculus
•    Data Handling
•    Mathematics Software
•    Critical Thinking and Problem-Solving
•    Learning Attitude

Fast Track Python For Data Science Objectives

Upon completion of the course, the professionals will be competent in the following areas:
•    Utilise computational and statistical methods to solve real-world issues and convey the outcomes in oral and written presentations.
•    Comprehend the significance of effective data management, the necessity of work documentation for results that can be replicated, and how to evaluate the ethical implications of a   data science project.
•    Write Python code following accepted conventions.
•    Design various plots and customizing them to be visually appealing and interpretable. 
•    Learn about the pandas DataFrame and dictionary, substitutes for the Python list. 
•    Construct and modify datasets and use these data structures to get information. 
•    Recognise and employ variables.
•    Deal with pandas DataFrames and basic Python data types such as integers, floats, strings, characters, lists, and dictionaries.
•    Employ fundamental flow control, such as conditionals and loop
•    Open text files and read data.
•    Access data files to acquire basic summary statistics.
•    Modify and take data out of pandas InfoFrames.
•    Proficiency in using computing tools for data analysis and statistical data analysis.

About The Certification

Following the three-day Fast Track Python for Data Science (TTPS4873) course, students will obtain a certification demonstrating their proficiency with Python databases, networked application program interfaces, and data structures. It attests to your proficiency in various capacities, from development and programming to strategic decision-making and analysis. The certification will be granted only when the learners complete the assignments or assessments that the training programme demands, attend all training sessions, and fully participate in all training activities. Employers utilize Python for Data Science certification to confirm that candidates can handle challenging assignments. Earning this credential will help you in your career as an embedded systems developer, web developer, data analyst, DevOps engineer, full stack developer, or Python developer.

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Training Options

Online Training

Virtual Instructor-Led Training

  • 2 days Instructor-led Online Training
  • Experienced Subject Matter Experts
  • Approved and Quality Ensured training Material
  • 24*7 leaner assistance and support

Corporate Training

Customized According To Team's Requirements

  • Blended Learning Delivery Model (Self-Paced E-Learning And/Or Instructor-Led Options)
  • Course, Category, And All-Access Pricing
  • Enterprise-Class Learning Management System (LMS)
  • Enhanced Reporting For Individuals And Teams
  • 24x7 Teaching Assistance And Support

Course Outline

•    Why Python?
•    Python in the Shell
•    Python in Web Notebooks (iPython, Jupyter, Zeppelin)
•    Demo: Python, Notebooks, and Data Science

•    Using variables
•    Builtin functions
•    Strings
•    Numbers
•    Converting among types
•    Writing to the screen
•    Command line parameters
•    Flow Control
•    About flow control
•    White space
•    Conditional expressions
•    Relational and Boolean operators
•    While loops
•    Alternate loop exits

•    About sequences
•    Lists and list methods
•    Tuples
•    Indexing and slicing
•    Iterating through a sequence

•    List comprehensions
•    Generator Expressions
•    Nested sequences
•    Working with Dictionaries

•    File overview
•    Opening a text file
•    Reading a text file
•    Writing to a text file
•    Reading and writing raw (binary) data

•    Defining functions
•    Parameters 
•    Global and local scope
•    Nested functions
•    Returning values

•    Sorting
•    Exceptions
•    Importing Modules
•    Classes
•    Regular Expressions

•    Math functions
•    The string module

•    Working with dates and times
•    Translating timestamps
•    Parsing dates from text
•    Formatting dates
•    Calendar data

•    Data Science Essentials
•    Pandas Overview
•    NumPy Overview
•    SciKit Overview
•    MatPlotLib Overview
•    Working with Python in Data Science

Course Reviews


Yes, students with different experience levels are catered to in the course. Although prior programming knowledge or expertise is advantageous, the course starts with fundamental ideas before moving on to more complex subjects. It is appropriate for novices since it offers a thorough grasp of Python and Data Science.

Students' assessments will be conducted through daily tasks, group projects, and a final test. The evaluation standards will encompass code accuracy, productivity, and quality.

Indeed, pursuing a career in Python development is a wise choice. One of the most widely used programming languages worldwide is Python. After JavaScript and HTML/CSS, Python was the third most used language worldwide in 2021, according to Statista.

The trainers get to use the lab 30 to 180 days after the training. A lab training key will be provided to each student so they may connect to a remote lab environment during class.

Vinsys offers the most outstanding and up-to-date knowledge in certification training since we have been offering technical courses for over 20 years. Notably, Vinsys has earned ISO 9001 certification, attesting to the high caliber of instruction it provides. Vinsys is an excellent location for training because of its outstanding support system and authorized training programs. After you sign up with us for the Python for Data Science certification course, you will receive the best training.

While there aren't any explicit qualifications, having a fundamental understanding of programming and basic data analysis proficiency techniques can be beneficial. However, it is not mandatory; prior training or work experience in the IT sector is preferable.

This course will make you a Python for Data Science pro expert in 03 days.

Vinsys provides adaptability in the way courses are delivered. There are three different ways to take the course: group instructor-led, virtual instructor-led, and instructor-led. The optimal choice for you will rely on your availability and areas of interest in studying.