Data Science And Machine Learning Course | DCode Institut

Data Science and Machine Learning Course at DCode Institute

Are you ready to enter one of the most in-demand fields today? DCode Institute’s Data Science and Machine Learning Course provides you with the skills, knowledge, and hands-on experience needed to become an expert in these rapidly growing fields.

  • 5.0
  • Certificate
  • All levels
  • Online
  • Offline
  • English-Hindi-Gujarati

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Course Description

Unlock the power of data and advance your career with DCode Institute’s Data Science and Machine Learning course. Designed for aspiring data scientists and professionals looking to upskill, this comprehensive program equips you with the knowledge and hands-on experience needed to excel in the rapidly growing fields of Data Science and Machine Learning.

Data Science is the backbone of modern decision-making, and Machine Learning is revolutionizing industries by enabling systems to learn from data and improve over time. This course offers in-depth training in both fields, blending theory with practical application through real-world projects.

Our expert instructors will guide you through each module with a structured, hands-on approach, ensuring you gain a thorough understanding of the core concepts and their real-world applications. The course is designed for students of all levels, whether you’re a beginner wanting to break into the field or a professional looking to enhance your data science and machine learning knowledge

What you’ll learn
  • Introduction to Data Science: Understand the importance of data science and its applications in today’s world.
  • Python for Data Science: Learn the programming fundamentals of Python, one of the most widely used languages in data science.
  • Data Preprocessing: Master techniques to clean and prepare datasets for analysis.
  • Machine Learning Algorithms: Gain practical knowledge of supervised and unsupervised machine learning algorithms.
  • Deep Learning: Dive into neural networks and frameworks like TensorFlow and Keras.
  • Data Visualization: Use tools like Matplotlib, Seaborn, and Tableau to create meaningful data visualizations.
  • Real-World Applications: Apply your skills in building real-world machine learning models and solving industry problems.
  • Tech Professionals: Those working in software development, engineering, or IT who wish to transition into data-driven roles.
  • College Graduates: Fresh graduates aiming to gain industry-relevant skills and break into the tech sector.

Overview of Data Science: Introduction to data science, its significance in various industries, and applications.
The Data Science Workflow: Understanding the end-to-end process—data collection, cleaning, analysis, modeling, and visualization.
Introduction to Machine Learning: What is machine learning? Key differences between supervised, unsupervised, and reinforcement learning.
Python for Data Science: Basics of Python, including syntax, data structures, and libraries used in data science.
NumPy for numerical computations.
Secure Network Architecture: Design and implement secure network infrastructures.
Pandas for data manipulation and analysis.
Data Collection: Sourcing data from different platforms and formats (CSV, JSON, databases, APIs).
Data Cleaning: Handling missing values, duplicates, outliers, and incorrect data.
Data Transformation: Scaling, encoding categorical variables, and feature engineering techniques.
Data Integration: Combining data from multiple sources for analysis.
Descriptive Statistics: Measures of central tendency (mean, median, mode), dispersion (variance, standard deviation).
Probability Theory: Basic probability concepts, conditional probability, Bayes’ theorem.
Inferential Statistics: Hypothesis testing, confidence intervals, t-tests, chi-square tests.
Correlation and Regression Analysis: Linear regression, multiple regression, and understanding relationships between variables.
Supervised Learning: Key algorithms like Linear Regression, Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machines (SVM).
Overfitting and Underfitting: Techniques to prevent overfitting (cross-validation, regularization).
Clustering: Introduction to K-Means, Hierarchical Clustering, and DBSCAN.
Dimensionality Reduction: Techniques like Principal Component Analysis (PCA) and t-SNE for reducing feature space while preserving important information.
Association Rule Learning: Apriori and Eclat algorithms for market basket analysis.
Introduction to Neural Networks: Understanding the structure of artificial neural networks (ANN), perceptron model.
Backpropagation and Training: How neural networks are trained using gradient descent.
Convolutional Neural Networks (CNNs): Applied in computer vision tasks (image classification, object detection).
Recurrent Neural Networks (RNNs): Applied in sequence data (time series, natural language processing).
Deep Learning Frameworks: Using TensorFlow and Keras to build and train deep learning models.
Advanced Visualization: Create interactive dashboards and advanced visualizations using Tableau, Plotly, and Dash.
Storytelling with Data: Learn how to present your analysis in a meaningful and engaging way.
Business Intelligence Tools: Introduction to tools like Power BI and Tableau for creating actionable insights.
Completion of Course Modules: You must successfully complete all the course modules, including programming exercises, hands-on labs, and quizzes.
Capstone Project: You will need to complete a Capstone Project, showcasing your ability to solve an end-to-end data science problem, from data collection to deployment.
Final Evaluation: Your final project and performance throughout the course will be evaluated by the instructors to ensure that you have mastered the core concepts and can apply them in real-world situations.
instructor-image

Vijay Patel

Data Science and Machine Learning course

  • 9.1k
  • 4.5
  • 29 Courses
  • 205
About Instructor

Vijay Patel is an experienced instructor and industry expert specializing in Data Science, Machine Learning, and Artificial Intelligence. With years of experience in both academia and the tech industry, Vijay brings a wealth of knowledge and practical expertise to his students at DCode Institute.

As the lead instructor for the Data Science and Machine Learning course, Vijay is dedicated to empowering students with the skills necessary to excel in the rapidly evolving field of data science. His teaching approach combines theory with hands-on practice, ensuring that students not only understand the foundational concepts but also gain the ability to apply them in real-world scenarios.

Our Student Reviews

4.5

(Based on todays review)

avatar
Amarsang Vaghela

2 days ago

" The Data Science and Machine Learning course at DCode Institute was a game-changer for me. Vijay Patel's practical teaching approach helped me grasp complex concepts like machine learning algorithms and deep learning. The hands-on projects and capstone gave me the confidence to apply these techniques in my job at Google. I highly recommend this course to anyone looking to break into data science."

avatar
Mukesh Solanki

1 days ago

"I had no prior experience in data science, but this course made everything so much easier to understand. Vijay’s clear explanations and patient support during the learning process made it fun. The course material was well-structured, and I loved working with real datasets to apply my knowledge. I’m now working as a data analyst, and I couldn’t have done it without DCode! "

avatar
Piyush Vaghela

2 days ago

" The Data Science and Machine Learning course was the best decision I made for my career. Not only did I learn machine learning and data analysis skills, but I also gained experience with data visualization tools like Tableau. Vijay Patel’s mentorship was invaluable, and I feel much more confident in applying these skills in my day-to-day work."

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Frequently Asked Questions

This course is designed for anyone who wants to build a career in Data Science, Machine Learning, or Artificial Intelligence. Whether you're a complete beginner, a software developer, or a business analyst looking to enhance your skillset, this course will equip you with the necessary tools and knowledge.

  • Programming Skills: Basic understanding of programming concepts is beneficial but not mandatory. We start from the very basics of Python.
  • Mathematics: A basic understanding of statistics and algebra will help, but we provide all the necessary mathematical background during the course.
  • Motivation to Learn: A willingness to engage in hands-on projects and assignments.

  • Live Online Classes: Interactive sessions with expert instructors (including Vijay Patel).
  • On-Demand Videos: Access to recorded sessions for revision at your convenience.
  • Hands-On Labs and Projects: Practical exercises and assignments for applying the knowledge in real-world scenarios.
  • Capstone Project: A final project where you apply what you've learned to a real-world data problem.

    • Yes! Upon successfully completing the Data Science and Machine Learning course, you will receive a Certificate of Completion from DCode Institute. This certificate is recognized by employers and adds value to your professional credentials.

  • Programming Languages: Python, R (optional)
  • Libraries/Frameworks: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras
  • Data Visualization: Tableau, Power BI, Matplotlib
  • Machine Learning Algorithms: Linear Regression, Logistic Regression, Decision Trees, KNN, SVM, Random Forest, and more
  • Deep Learning: Neural Networks, CNN, RNN

  • Data Scientist
  • Machine Learning Engineer
  • Data Analyst
  • Business Intelligence Analyst
  • AI Specialist
  • Data Engineer

    • No, all the tools and software required for the course are free and open-source. You will need to install Python, Jupyter Notebook, and libraries like Pandas, NumPy, and Scikit-learn (we’ll guide you on how to set everything up).

    Yes! Our Data Science and Machine Learning course is available to students worldwide. Since the course is conducted online, you can join from anywhere and learn at your own pace.
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    This course includes

    • Skills Beginner
    • Language English
    • Certificate Yes

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