Overview of Course

Our Data Science Training course is designed to help you learn the essential skills required for a career in data science. This course covers key topics such as data analysis, machine learning, and statistical modeling. Through our comprehensive curriculum, you will gain hands-on experience in real-world data science projects and build a strong foundation in this dynamic field.

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Course Highlights

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Comprehensive coverage of the data science workflow

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Hands-on experience with real-world projects

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Use of popular data science tools such as Python, SQL, and Tableau<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


Data analysis and visualization


Data cleaning and preprocessing


Statistical modeling


Machine learning techniques


Python programming


SQL database management


Tableau for data visualization

Training Options

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1-on-1 Training

USD 350 / INR 30000
  • 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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  • Keep employees up-to-date with changing industry trends and advancements.
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  • Improve employee morale, job satisfaction, and retention rates.
  • Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
  • Obtain long-term organizational growth and success.

Course Reviews


  • Introduction to Data Science
  • Understanding Data
  • Data Exploration Techniques
  • Data Preprocessing Techniques
  • Introduction to Data Mining

  • Introduction to Python
  • Python Data Types
  • Control Structures in Python
  • Functions and Modules in Python
  • Object-Oriented Programming in Python

  • Introduction to Data Structures
  • Lists, Tuples and Dictionaries
  • Arrays and Matrices
  • Data Manipulation using Pandas Library
  • File Handling in Python

  • Introduction to Data Visualization
  • Matplotlib Library
  • Seaborn Library
  • Plotly Library
  • Data Visualization using Tableau

  • Descriptive Statistics
  • Probability Distributions
  • Statistical Inference
  • Hypothesis Testing

  • Introduction to Machine Learning
  • Types of Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

  • Introduction to Logistic Regression
  • Logistic Regression Algorithm
  • Types of Logistic Regression
  • Evaluating Logistic Regression Model

  • Introduction to Decision Trees
  • Types of Decision Trees
  • Decision Tree Algorithm
  • Random Forest Algorithm

  • Introduction to Unsupervised Learning
  • K-Means Clustering
  • Hierarchical Clustering
  • Principal Component Analysis (PCA)
  • Anomaly Detection

  • Introduction to Natural Language Processing
  • Text Preprocessing
  • Text Classification
  • Text Clustering
  • Sentiment Analysis

  • Linear Algebra
  • Calculus
  • Probability Theory
  • Optimization
  • Numerical Analysis

  • Introduction to Scipy Library
  • Scipy Sub-packages
  • Linear Algebra using Scipy
  • Numerical Optimization using Scipy
  • Integration and Differential Equations using Scipy

  • Introduction to Apache Spark
  • Setting up Spark Environment in Python
  • Spark RDD Operations
  • Spark DataFrames
  • Spark Streaming

  • Introduction to Deep Learning
  • Artificial Neural Networks
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Deep Learning using TensorFlow

  • Introduction to Keras and TensorFlow
  • Setting up Environment for Keras and TensorFlow
  • Building Neural Networks using Keras and TensorFlow
  • Hyperparameter Tuning
  • Saving and Loading Models

  • Introduction to Restricted Boltzmann Machine
  • Energy-Based Models
  • Training Restricted Boltzmann Machine
  • Introduction to Autoencoders
  • Autoencoder Architecture

  • Introduction to Big Data
  • Hadoop Architecture
  • Setting up Hadoop Environment
  • MapReduce Programming in Hadoop
  • Spark Architecture

  • Introduction to Tableau
  • Data Visualization using Tableau
  • Tableau Data Types
  • Tableau Calculations
  • Tableau Dashboards

  • Introduction to MongoDB
  • MongoDB Data Model
  • CRUD Operations in MongoDB
  • Indexing and Aggregation in MongoDB
  • MongoDB with Python

  • Introduction to SAS
  • SAS Data Sets
  • SAS Programming
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  • RedtickGet a perspective with a glimpse of what the learning process entails.
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Inquiry for :


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Target Audience:

  • Individuals looking to start a career in data science
  • Data analysts seeking to upgrade their skills
  • Software developers interested in machine learning and data science
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  • Basic knowledge of programming
  • Familiarity with statistics and linear algebra
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Benefits of the course:

  • Gain in-demand skills for a high-paying career in data science
  • Learn from experienced data scientists
  • Build a strong foundation in data science
  • Work on real-world projects to gain practical experience
  • Use popular data science tools such as Python, SQL, and Tableau
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Exam details to pass the course:

  • There is no exam to pass this course.
  • However, you will be required to complete the real-world projects and assignments to earn a certificate of completion.
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Certification path:

  • Upon successful completion of the course, you will receive a certificate of completion from Skillzcafe.
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Career options after doing the course:

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • Data Engineer
  • Analytics Manager

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Comprehensive coverage of the data science workflow
  • Bullet Icon Hands-on experience with real-world projects
  • Bullet Icon Expert instruction from experienced data scientists
  • Bullet Icon Practical experience in data cleaning, preprocessing, and advanced machine learning techniques
  • Bullet Icon Use of popular data science tools such as Python, SQL, and Tableau


The course duration is 50 hours.

No, prior experience in data science is required. However, basic knowledge of programming and familiarity with statistics and linear algebra will be beneficial.

You will work on real-world data science projects that will help you gain practical experience and apply the skills you learn in the course.

Yes, upon successful completion of the course, you will receive a certificate of completion from Skillzcafe.

You will receive expert instruction from experienced data scientists throughout the course, and our support team is available to assist you with any questions or issues you may encounter.

This course is instructor-led, meaning you will have access to experienced data scientists who will guide you throughout the course.

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

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