Data Science and Machine Learning for Beginners with Python is a training program that introduces students to the Python programming language for Data Science and Machine Learning. Python is a flexible, general-purpose, and object-oriented programming language that is used for a wide range of tasks. Python is widely utilized in Data Science. A variety of concepts, programming languages, and frameworks are related to Machine Learning.
The course is designed for all levels of learners. Those who have no prior experience working with Python can take this course and learn Python programming and its application to Data Science and Machine Learning. The course is usually available for INR 1,999 on Udemy but you can click now to get the Data Science and Machine Learning for Beginners with Python Course for INR 449.
Who all can opt for this course?
- Novice Data Scientists
- Machine learning Beginners
- Python Beginners
- SQL Beginners
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 8 hours |
| Rating | 3.8/5 |
| Student Enrollment | 30,039 students |
| Instructor | Bluelime Learning Solutions https://www.linkedin.com/in/bluelimelearningsolutions |
| Topics Covered | Python fundamentals, Data Science, Machine Learning with Python, PostgreSQL, Big Data |
| Course Level | Beginner |
| Total Student Reviews | 522 |
Learning Outcomes
- Install Jupyter Notebook Server
- Learn how to create a fresh notebook
- Explore Jupyter Notebook’s Components
- Understand the Data Science lifecycle
- Use Kaggle Data Sets
- Perform Probability Sampling
- Explore and use tabular data
- Explore Pandas DataFrame
- Manipulate Pandas DataFrame
- Data Cleaning
- Data Visualization
- Visualize qualitative data
- Explore Machine Learning frameworks
- Become familiar with supervised Machine Learning
- Use Machine Learning to predict a house’s worth
- Use Scikit-Learn
- Load datasets
- Make predictions using Machine Learning
- Learn about Python Expressions and Statements
- Learn about Python Data Types and how to cast data types
- Understand Python Variables and Data Structures
- Understand Python Conditional Flow and Functions
- SQL with PostgreSQL
- Perform SQL CRUD Operations on PostgreSQL Database
- Filter and Sort Data using SQL
- Big Data terminologies
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Introduction and Setup (42 minutes) | Introduction |
| What is Jupyter Notebook | ||
| Installing Jupyter Notebook Server | ||
| Running Jupyter Notebook Server | ||
| Common Jupyter Notebook Commands | ||
| Jupyter Notebook Components | ||
| Jupyter Notebook Dashboard | ||
| Jupyter Notebook User Interface | ||
| Creating a new Notebook | ||
| 2. | Python Fundamentals (01 hour 40 minutes) | What is Python |
| Python Expressions | ||
| Python Statements | ||
| Python Comments | ||
| Python Data Types | ||
| Casting Data Type | ||
| Python Variables | ||
| Python List | ||
| Python Tuple | ||
| Python Dictionaries | ||
| Python Operators | ||
| Python Conditional Statements | ||
| Python Loops | ||
| Python Functions | ||
| 3. | Data Science (01 hour 46 minutes) | What is Data Science |
| Impact of Data Science | ||
| Data Science life cycle | ||
| Data Science Terminologies | ||
| Kaggle Data Sets | ||
| Probability Sampling | ||
| Tabular Data | ||
| Exploring Pandas DataFrame | ||
| Manipulating a Pandas DataFrame | ||
| What is Data Cleaning | ||
| Basic Data Cleaning Process | ||
| What is Data Visualization | ||
| Visualizing Qualitative Data : Part 1 | ||
| Visualizing Qualitative Data : Part 2 | ||
| 4. | Introduction to Machine Learning with Python (01 hour 38 minutes) | Installing Python |
| Installing Pycharm on Windows | ||
| Installing Pycharm on Macs | ||
| Installing Anaconda | ||
| What is Machine Learning | ||
| Machine Learning Frameworks | ||
| Machine Learning Vocabulary | ||
| Supervised machine learning | ||
| Where Machine Learning is used | ||
| Creating a basic house value estimator | ||
| Using Scikit-Learn | ||
| Loading a dataset part 1 | ||
| Loading a dataset part 2 | ||
| Making Predictions part 1 | ||
| Making Predictions part 2 | ||
| 5. | SQL and Data Science with PostgreSQL (01 hour 37 minutes) | What is SQL |
| What is PostgreSQL | ||
| Installing PostgreSQL on windows | ||
| Installing PostgreSQL on Mac | ||
| Connecting to a PostgreSQL Database | ||
| Database Concepts | ||
| Install Sample Database | ||
| What is CRUD | ||
| Data Types | ||
| SQL CREATE TABLE Statement | ||
| SQL INSERT Statement | ||
| SQL SELECT Statement | ||
| SQL UPDATE Statement | ||
| SQL WHERE clause | ||
| SQL ORDER BY Clause | ||
| 6. | Introduction to Big Data Terminology (29 minutes) | What is Big Data |
| What is high volume | ||
| What is high variety | ||
| What is high velocity | ||
| Google’s Big Data Approach | ||
| What is a cluster | ||
| What is a Node | ||
| Google File System | ||
| Google’s Big Table | ||
| What is MapReduce | ||
| Apache Hadoop | ||
| Thank You |
Resources Required
No prior experience is required to enroll in this course. The instructor will walk through the steps of the software installation and setup.
Featured Review
Prishabh Dwivedi (4/5): Good for a beginner but, should include some hands-on approach which was lacking in this.
Pros
- Edson Maciel (4/5): This is a good course for beginners to learn to use python
- Shivam Arora (3/5): This course is good but can be more focused on data science and machine learning
- Vladimir Jimenez (4/5): I would have liked to see more hands-on than theory.
- Devanshi Doshi (4/5): It was good but resources weren’t available to download so should try that it could be.
Cons
- Vera S. (3.5/5): It is a good course, however, I found it slow at moments and a lot of different topics mentioned but not really focused on machine learning with Python, which I was expecting.
- Bjorn C. (2.5/5): It was okay for an absolute beginner but the material jumps around a lot and there is little in the way of hands-on exercises. Also a lot of typos in the slides which makes me question how much time was really spent designing the course. There are better Intro to DS classes out there, to be blunt.
- Tham J. (2.5/5): The course focuses more on explanation and lack of hands-on.
- Giulia S. (1/5): Very slow, explains you every step even for clicking “next” on the install window.
About the Author
The course is offered by Bluelime Learning Solutions. They offer over 438 courses and have a 4.1 instructor rating and 36,972 reviews on Udemy. They have taught 7,46,303 students so far.
- Bluelime is situated in the UK and develops high-quality, simple-to-understand eLearning solutions.
- They provide practical knowledge by using examples from everyday life.
- Bluelime has worked on a variety of projects for Fortune 500 organizations and is aware of what is needed to give students the necessary preparation.
Comparison Table
| Parameters | Data Science and Machine Learning For Beginners with Python | Binomial, Normal Distribution, and Matrices for Data Science | Logistic Regression in Python |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 8 hours | 16.5 hours | 7.5 hours |
| Rating | 3.8/5 | 4.3 /5 | 4.5 /5 |
| Student Enrollments | 30,039 | 46,412 | 98,752 |
| Instructors | Bluelime Learning Solutions | Sai Acuity Institute of Learning Pvt Ltd Enabling Learning Through Insight! | Start-Tech Academy |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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