50 Hrs
3221+ Enrollments
Data Science Training
This Data Science Training course is an all-inclusive program that will equip you with the skills and knowledge necessary to become a successful data scientist. The course covers the entire data science workflow, from data cleaning and preprocessing to advanced machine learning techniques. You will learn to use popular data science tools such as Python, SQL, and Tableau, and gain practical experience by working on real-world projects. Our experienced instructors will guide you every step of the way, ensuring that you have the necessary skills to succeed in the data science field.
Data Science Training
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.
Course Highlights
Comprehensive coverage of the data science workflow
Hands-on experience with real-world projects
Use of popular data science tools such as Python, SQL, and Tableau<br /><br />
Key Differentiators
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
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
1-on-1 Training
Access to live online classes- Flexible schedule including weekends
- Hands-on exercises with virtual labs
- Session recordings and learning courseware included
- 24X7 learner support and assistance
- Book a free demo before you commit!
Corporate Training
- Everything in 1-on-1 Training plus
- Custom Curriculum
- Extended access to virtual labs
- Detailed reporting of every candidate
- Projects and assessments
- Consulting Support
- Training aligned to business outcomes
Unlock Organizational Success through Effective Corporate Training: Enhance Employee Skills and Adaptability- Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
- Keep employees up-to-date with changing industry trends and advancements.
- Adapt to new technologies & processes and increase efficiency and profitability.
- 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
Curriculum
- 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
- ANOVA
- 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
Meet the instructor and learn about the course content and teaching style.- Make informed decisions about whether to enroll in the course or not.
- Get a perspective with a glimpse of what the learning process entails.
Description
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
Prerequisite:
- Basic knowledge of programming
- Familiarity with statistics and linear algebra
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
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.
Certification path:
- Upon successful completion of the course, you will receive a certificate of completion from Skillzcafe.
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:
Comprehensive coverage of the data science workflow- Hands-on experience with real-world projects
- Expert instruction from experienced data scientists
- Practical experience in data cleaning, preprocessing, and advanced machine learning techniques
- Use of popular data science tools such as Python, SQL, and Tableau
FAQs
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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