Data Science with Python Course

Planning to pursue your career in the data science roles? Then this Data Science with Python course will let you on the way. Learning python is the first crucial step to enter into the world of data science and with our team of expert trainers, you’ll learn the concepts of python programming. Adding to this, with our blended learning approach, you’ll learn data science concepts such as mathematical computing, data wrangling, etc. <br /> So, Register for Hatigen’s Data Science with Python Course and drive on your dream career path.

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Data Science with Python Online Course – Overview

This Data Science with Python Course allows you to learn the concepts of python, machine learning, data analysis, web scraping, data visualization, and NLP. Join our Data Science with python certification training program and master the most important data science tools using python.

Data Science with Python Online Certification Training – Key Features

  • Trusted content
  • Re-learn for free anytime in a year
  • Rigorous assignments and assessments
  • Learn at your own pace
  • Mandatory feedback sessions
  • Mock-interviews
  • Hands-on real-time experience
  • Free mentorship
  • Live chat for instant solutions
  • Job-ready employees post-training
  • End-to-end training
  • Download the certificate after the course
Data Science with Python Online Certification Training – Skills Covered: Data wrangling. Data exploration. Data visualization. Mathematical computing. Web scraping. Hypothesis building. Python programming concepts. NumPy and SciPy package. ScikitLearn package for Natural Language Processing.

Data Science with Python Online Course – Benefits

With the increasing demand, the market for python software in the field of data science is known to experience a huge growth by 2025. Also, with a CAGR of 30%, the global market growth of Data Science is expected to reach $140.9 billion by 2024.

Designation
Annual Salary
Hiring Companies
Job Wise Benefits
Designation
Data Scientist

UK
Hiring Companies
Designation
Data Analyst

UK
Hiring Companies

Data Science with Python Online Course – Training Options

Self-Paced Learning

£ 1200

  • 1-year access to the Blockchain course content
  • 1 capstone project
  • Multiple assessments
  • Continuous feedback sessions
  • Access to the class recordings
  • Assistance and support
  • Download certification
  • Free mentorship

Online Boot Camp

£ 1000

  • Everything in Self-paced learning +
  • On-spot doubt clarification
  • Interactive training sessions
  • Sessions on the capstone project
  • Live, online classroom training
  • Mock-interviews

Corporate Training

Customized to your team's needs

  • 1-year access to the Blockchain course content
  • 1 capstone project
  • Multiple assessments
  • Continuous feedback sessions
  • Class recordings
  • Assistance and support
  • Certification after the course

Data Science with Python Training Program – Curriculum

Eligibility

If you are interested and willing to work in the analytics field, then this data science with python course is for you. It is suitable for all levels of experience with a genuine interest in data science, and due to its high demand, it has turned out to be a great career option.

Pre-requisites

Before you begin this Data Science with Python training course, it is essential that you have an understanding of the basic concepts. So, get to know about the concepts of statistics, math refresher, introduction to python programming and data science, etc. However, this data science with python course online will allow you to learn the concepts from the scratch.

Course Content

  • 1.01 Course Introduction
  • 1.02 Demo: Jupyter Lab Walk - Through
  • 2.01 Learning Objectives
  • 2.02 Data Science Methodology
  • 2.03 From Business Understanding to Analytic Approach
  • 2.04 From Requirements to Collection
  • 2.05 From Understanding to Preparation
  • 2.06 From Modeling to Evaluation3
  • 2.07 From Deployment to Feedback
  • 2.08 Key Takeaways
  • 3.01 Learning Objectives
  • 3.02 Python Libraries for Data Science
  • 3.03 Import Library into Python Program
  • 3.04 Numpy
  • 3.05 Demo: Numpy
  • 3.06 Pandas
  • 3.07 Series
  • 3.08 DataFrame
  • 3.09 Demo Pandas: Part One
  • 3.10 Demo Pandas: Part Two
  • 3.11 Matplotlib
  • 3.12 Demo: Matplotlib
  • 3.13 SciPy
  • 3.14 Demo: Scipy
  • 3.15 Scikit learn
  • 3.16 Demo: Scikit learn
  • 3.17 Web Scraping with Beautiful Soup
  • 3.18 Parser
  • 3.19 Demo: Web Scraping with Beautiful Soup
  • 3.20 Key Takeaways
  • 4.01 Learning Objectives
  • 4.02 Data Exploration Loading Files: Part A
  • 4.03 Data Exploration Loading Files: Part B
  • 4.04 Data Exploration Techniques: Part A
  • 4.05 Data Exploration Techniques: Part B
  • 4.06 Seaborn
  • 4.07 Demo: Correlation Analysis
  • 4.08 Data Wrangling
  • 4.09 Missing Values in a Dataset
  • 4.10 Outlier Values in a Dataset
  • 4.11 Demo: Outlier and Missing Value Treatment
  • 4.12 Data Manipulation
  • 4.13 Functionalities of Data Object in Python: Part A
  • 4.14 Functionalities of Data Object in Python: Part B
  • 4.15 Different Types of Joins
  • 4.16 Key Takeaways
  • 5.01 Learning Objectives
  • 5.02 Introduction to Feature Engineering
  • 5.03 Encoding of Catogorical Variables
  • 5.04 Label Encoding
  • 5.05 Techniques used for Encoding variables
  • 5.06 Key Takeaways
  • 6.01 Learning Objectives
  • 6.02 Types of Plots
  • 6.03 Plots and Subplots
  • 6.04 Assignment 01: Pairplot Demo
  • 6.05 Assignment 02: Pie Chart Demo
  • 6.06 Key Takeaways
  • 7.01 Learning Objectives
  • 7.02 Feature Selection
  • 7.03 Regression
  • 7.04 Factor Analysis
  • 7.05 Factor Analysis Process
  • 7.06 Principal Component Analysis (PCA)
  • 7.07 First Principal Component
  • 7.08 Eigenvalues and PCA
  • 7.09 Demo: Feature Reduction
  • 7.10 Linear Discriminant Analysis
  • 7.11 Maximum Separable Line
  • 7.12 Find Maximum Separable Line
  • 7.13 Demo: Labeled Feature Reduction
  • 7.14 Key Takeaways
  • IBM HR Analytics Employee Attrition Modeling

Data Science with Python Training Online – FAQs

Renowned as a high-level programming language, python is easy to read, learn, and write. Furthermore, due to its easy-to-follow indentation system, it is a highly preferred language for most programmers and data scientists.

With the advancement in the technologies and evolution in the learning methodologies, one can learn Python Data Science courses with ease and efficiency. It allows you to learn at your own pace with provided study material and live classes from anywhere and at any time. Hatigen also delivers you year-around support through our mentors dedicated to solving all of your conceptual doubts.

If you have any basic knowledge of coding concepts, then you can grasp the technicalities of python programming easily. However, it is not a compulsion as python programming is regarded as a beginner’s language. Anyone who wants to enter into the software field with no coding background can learn python programming easily and expand their career opportunities with other advanced courses and technologies such as data science.

Python is also an object-oriented programming language and due to its simple syntax, anyone can easily understand python. Furthermore, as the prototypes are similar to Java or C++, with the knowledge of these programming languages, you can learn python faster. Therefore, you can easily switch to python and expand your career opportunities through this Data Science with Python course.

As python is used to develop numerous applications, it includes a variety of modules and libraries. However, you need not be familiar with all the modules and libraries. Therefore, basic knowledge of Python is enough to start with this comprehensive course, and in this data science with python certification course, you will learn all the modules and libraries required for data science projects.

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