Python Programming for Beginners in Data Science course, as the name suggests, focuses on just enough Python programming required to work any Machine Learning techniques. Python is one of the key skills for any Data Scientist; however, most Data Scientists do not have the required experience in Python programming.
Therefore, Python Programming for Beginners course walks through essential concepts of Python needed for Data Science including variables, type conversions, flow control, operators, loops, strings, object-oriented programming, etc. The courses are usually available at INR 3,499 on Udemy but you can click now to get 87% off and get Python Programming for Beginners in Data Science Course for INR 449.
Who all can opt for this course?
- People who want to study Python as their first language but are not programmers
- Those who are interested in data science and machine learning
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 14 hours |
| Rating | 4.4/5 |
| Student Enrollment | 1,22,250 students |
| Instructor | Ajay Tech https://www.linkedin.com/in/ajaytech |
| Topics Covered | Python Basics, Flow Control, Loops, Strings, Functions, Objected Oriented Python |
| Course Level | Beginner |
| Total Student Reviews | 3,107 |
Learning Outcomes
- Learn Python programming to perform data science, machine learning, and deep learning functions
- Possess a solid understanding of the fundamentals of Python
- Create a solid programming foundation so you can use it with machine learning algorithms
- Learn object-oriented Python programming
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Day 0 – Python Setup (49 minutes) | Why Python |
| About the Course | ||
| Python Setup | ||
| Hello World in Python | ||
| Python IDE Setup | ||
| Print Hello world on the console | ||
| 2. | Day 1 – Python Basics (01 hour 46 minutes) | What are Variables |
| Variables – Types of Numbers | ||
| Variables – Strings, Boolean & Reserved Keywords | ||
| Variables Quiz | ||
| Variables – Quiz | ||
| Assign variables | ||
| Swap two variables in Python | ||
| Variables – Recap | ||
| Variables – Challenge – Discussion | ||
| Type Conversion | ||
| Type Conversion Quiz | ||
| Type conversion Coding Exercise | ||
| Correct errors in Type Conversion | ||
| Type Conversion Quiz Discussion | ||
| Arithmetic Operators | ||
| Comparision Operators | ||
| Comparison operators quiz | ||
| Operator Precedence | ||
| Operator Precedence Quiz | ||
| Logical Operators | ||
| Combine Logical operators | ||
| 3. | Day 1 (contd) – Flow Control (01 hour 00 minutes) | if statement |
| python blocks | ||
| Find out if a number is positive, negative or zero | ||
| nested if statement | ||
| elif statement | ||
| else statement | ||
| flow control quiz – discussion | ||
| flow control challenges – discussion | ||
| if statement – Find the oldest students among the three | ||
| 4. | Day 2 – Loops (01 hour 08 minutes) | for loop |
| Odd numbers between 1 and 20 | ||
| While loop | ||
| Sum of numbers from 1 to 1000 | ||
| Operator Precedence Exercise | ||
| Challenge Discussion – 1 | ||
| Challenge Discussion – 2 | ||
| Challenge Discussion – 3 | ||
| for vs while loop | ||
| Break Statement – Theory | ||
| Break Statement – Program | ||
| for-else statement | ||
| Nested loops | ||
| 5. | Day 3 – Strings & Functions (01 hour 56 minutes) | What are Strings |
| Sub-strings | ||
| Split strings | ||
| Strip strings | ||
| Other String Functions | ||
| Cheatsheet | ||
| Challenges | ||
| Python Functions | ||
| Create your own Function | ||
| Nth Fibonacci Number | ||
| Sum of numbers divisible by 5 between any two given numbers | ||
| doc string | ||
| function arguments | ||
| Python functions – Summary | ||
| Python Built-in Functions | ||
| Python Built-in functions Summary | ||
| Sum of all alternate odd numbers | ||
| First Prime Numbers between a given range of numbers | ||
| Print a pattern | ||
| Reverse a string | ||
| 6. | Day 4 – Data Structures – Lists (02 hours 28 minutes) | What are Lists |
| Challenge | ||
| List Indexing and Merging | ||
| List Manipulation | ||
| Challenge – Average Grades v3 | ||
| Challenge contd. | ||
| Challenge contd. | ||
| Nested Lists | ||
| Enumerate Lists | ||
| Merge and Sort Lists | ||
| List Slicing | ||
| Python Dictionary | ||
| get-vs-index | ||
| Challenge – Vowels | ||
| Dictionary access | ||
| Dictionary – Key & Value objects | ||
| Challenge – 1 | ||
| Challenge – 2 | ||
| Challenge – 2 ( contd) | ||
| Dictionary – Deletion | ||
| Parts of an URL | ||
| 7. | Day 5 – Data Structures (contd.) (01 hour 06 minutes) | Python Tuples |
| Python Tuples ( contd. ) | ||
| Python Sets | ||
| Set Operations (Union, Intersection, Difference etc ) | ||
| Python Sets – (contd) | ||
| Python Sets – Summary | ||
| 8. | Day 6 – Object Oriented Python (29 minutes) | What is Object Oriented Python |
| Write your first Python Class | ||
| Attributes & Methods in a class | ||
| 9. | Day 7 – I/O & Exceptions (28 minutes) | I/O – Input / Output |
| I/O – contd. | ||
| Exceptions | ||
| 10. | Day 8 – Python Standard Library (01 hour 32 minutes) | Date Object |
| Quiz Discussion | ||
| Time delta | ||
| Time | ||
| Date time | ||
| File Operations – Read files | ||
| File operations – Write & Append files | ||
| File Operations – Exception Handling | ||
| Math Module | ||
| 11. | NumPy – Numeric Python (01 hour 09 minutes) | What is NumPy |
| What makes NumPy faster | ||
| How to Create Arrays in NumPy | ||
| How to Reshape NumPy Arrays | ||
| NumPy Array Creation | ||
| Element wise operations in NumPy | ||
| Aggregate Operations in NumPy | ||
| Array Indexing in NumPy | ||
| Array Slicing in NumPy | ||
| Append rows/columns in NumPy | ||
| Insert rows/columns in NumPy | ||
| Array Manipulation in NumPy | ||
| 12. | Pandas (13 minutes) | What is Pandas |
| Pandas Installation & Sample file creation | ||
| Dataframe Creation methods | ||
| 13. | Frequently Asked Questions (10 seconds) | Course Completion Certificate |
| 14. | Troubleshooting (18 seconds) | Jupyter command not recognized |
Resources Required
- A computer or Mac with an effective internet connection
- You can download every piece of necessary software, including the Python executable and integrated development environment
Positive Review
Iman Pourbaba (5/5): I think it is a wonderful class for data and python
Pros
- Bamidele Temitope Oluwafemi (5/5): Yes, it is the perfect course for aspiring Data scientists like myself
- Ashok Kumar Orupalli (4/5): It’s very good to get an idea to start working on data science.
- Jay Kothadia (5/5): Very good course for beginners and even for those who don’t have a coding background.
- Hardeep Singh (5/5): Very good explanation, very good experience to teach, I like it
Cons
- Barbara Aires Marques (1/5): It’s not engaging at all! A lot of confusing notes, lots of repeating, several misplanning and mistyping can potentially prejudice someone that is trying to follow the thinking to learn.
About the Author
The course is instructed by Ajay Tech. It is an IT company focusing on major areas like Data Science and Machine Learning. With a 4.4 instructor rating and 6,338 reviews on Udemy, the company offers 7 courses and has taught 2,32,044 students so far.
- Data Science, Machine Learning, Deep Learning, and Artificial Intelligence are the main areas of focus of Ajay Tech, an IT training organization.
- Their main priority is making learning simple.
- Therefore, every one of their courses is designed keeping novices in mind.
- There are some R versions, however, Python is the primary computer language they utilize to teach all of the courses.
Comparison Table
| Parameters | Python Programming for Beginners in Data Science | Decision Trees, Random Forests, AdaBoost & XGBoost in Python | The Art of Doing: Code 40 Challenging Python Programs Today! |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 14 hours | 7 hours | 28.5 hours |
| Rating | 4.4 /5 | 4.6 /5 | 4.8 /5 |
| Student Enrollments | 122,250 | 117,882 | 74,808 |
| Instructors | Ajay Tech | Start-Tech Academy | Michael Eramo |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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