Overview of Course

Data Science with Python Training is an advanced-level course designed for individuals seeking to enhance their skills in data science, statistics, and programming. This course will equip you with the knowledge and skills necessary to tackle complex data challenges using Python programming language.

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Course Highlights

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Hands-on experience with real-world datasets

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In-depth knowledge of data analysis, data visualization, and machine learning algorithms

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Expert-led training with personalized guidance and support<br /><br />

Key Differentiators

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    Personalized Learning with Custom Curriculum

    Training curriculum to meet the unique needs of each individual

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    Trusted by over 100+ Fortune 500 Companies

    We help organizations deliver right outcomes by training talent

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    Flexible Schedule & Delivery

    Choose between virtual/offline with Weekend options

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    World Class Learning Infrastructure

    Our learning platform provides leading virtual training labs & instances

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    Enterprise Grade Data Protection

    Security & privacy are an integral part of our training ethos

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


Understanding of data analysis, data visualization, and machine learning algorithms


Proficiency in Python programming language


Ability to use Python libraries for data manipulation, cleaning, and analysis


Knowledge of data preprocessing techniques and statistical analysis


Hands-on experience with real-world datasets and practical data science projects

Training Options

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1-on-1 Training

On Request
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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Course Reviews


  • Operating system requirements
  • Installing required software and libraries
  • Configuration and setup instructions
  • Troubleshooting common issues

  • Introduction to Python programming language
  • Basic syntax and data types
  • Control structures (loops and conditional statements)
  • Functions and modules
  • Input/output operations

  • Object-oriented programming (OOP) in Python
  • Working with classes and objects
  • Inheritance and polymorphism
  • Exception handling
  • Best practices in Python programming

  • Introduction to web scraping and web crawling
  • Basics of HTML and CSS
  • Using Python libraries for web scraping (e.g. BeautifulSoup, Requests)

  • Advanced web scraping techniques (e.g. dynamic web pages, cookies)
  • Using APIs to access web data
  • Working with JSON and XML data formats

  • Introduction to databases and database management systems
  • Types of databases (relational, NoSQL, etc.)
  • Data modeling and schema design
  • Data normalization

  • Introduction to SQL (Structured Query Language)
  • Querying and modifying data in a relational database
  • Joins, subqueries, and aggregation functions
  • Creating and managing database objects (tables, indexes, views, etc.)

  • Introduction to data analysis and visualization
  • Data exploration and cleaning
  • Data visualization with Python libraries (e.g. Matplotlib, Seaborn)

  • Advanced data visualization techniques (e.g. interactive visualizations, geospatial data)
  • Exploratory data analysis (EDA)
  • Statistical analysis and hypothesis testing

  • Machine learning for data analysis and prediction
  • Supervised and unsupervised learning algorithms
  • Model selection and evaluation
  • Model deployment and monitoring

  • Introduction to network analysis
  • Types of networks (social, transportation, communication, etc.)
  • Network modeling and representation
  • Network metrics and analysis techniques

  • Introduction to machine learning
  • Types of machine learning algorithms (supervised, unsupervised, reinforcement learning)
  • Feature selection and engineering
  • Model training and evaluation

  • Advanced machine learning techniques (e.g. deep learning, ensemble methods)
  • Neural networks and deep learning frameworks (e.g. TensorFlow, PyTorch)
  • Natural language processing (NLP) and computer vision
  • Best practices in machine learning
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Target Audience:

  • Professionals seeking to enhance their data science skills
  • IT professionals interested in data science and machine learning
  • Students pursuing a career in data science
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  • Basic knowledge of programming concepts
  • Familiarity with mathematics and statistics is an added advantage
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Benefits of the course:

  • Enhance your skills in data science, statistics, and programming
  • Learn from industry experts with years of experience in the field
  • Hands-on experience with real-world datasets
  • Opportunity to work on a capstone project
  • Certificate of completion upon successful completion of the course
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Exam details to pass the course:

  • There is no formal exam to pass the course.
  • However, you will be required to complete a capstone project to demonstrate your proficiency in data science and Python programming.
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Certification path:

  • Upon successful completion of the course, you will receive a certificate of completion from Skillzcafe.
  • However, there are no other certifications required to learn this course.
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Career options after doing the course:

  • Data Analyst
  • Data Scientist
  • Machine Learning Engineer
  • Business Analyst
  • Data Engineer

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Experienced trainers with years of industry experience
  • Bullet Icon Comprehensive coverage of data science concepts and Python programming language
  • Bullet Icon Hands-on experience with real-world datasets and practical projects
  • Bullet Icon Flexible learning options with online and offline training modes
  • Bullet Icon Certificate of completion upon successful completion of the course


The course duration is approximately 55 hours.

Yes, you will have lifetime access to the course material after completing the course.

Yes, you will need to install Python and Anaconda on your computer to complete this course.

You will work on a capstone project at the end of the course, where you will apply your data science skills to solve a real-world problem.

Basic knowledge of programming concepts is recommended, and familiarity with mathematics and statistics is an added advantage.

Yes, Skillzcafe offers a 30-day money-back guarantee if you are not satisfied with the course.

Yes, this course is suitable for beginners in data science who have basic programming knowledge. The course covers the essential concepts of data science and Python programming from scratch.

Yes, you will receive personalized guidance and support from our experienced trainers throughout the course. You can also reach out to our support team for any queries or issues during the course.

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