Complete Python Course(Bundle)
Python gives tremendous versatility, giving Python developers the freedom to enter a wide range of applications from software development, machine learning, data science, and web development. Learn complete Python course today and give your career a new dimension.-
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4.7/5
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4.7/5 (16287)
What you will learn
- Why Python is Important
- Transition from Python2 to Python3
- Installation of Python
- How to use your machine to code online
- Build your 1st Python code
- Constants, Reserved Words, & Variables
- Data Types in Python
- Using Conditions in Python
- Using Comparisons in Python
- Functions in Python
- Loops in Python
- Iterations in Python
- Introduction to Data Structure
- Strings & Functions
- Handling files in Python
- List & Dictionaries
- Sets & Tuples
- Constructors
- Inheritance & Polymorphism
- Regressions in Python
- Clustering and Cluster Analysis
- Linear Regression using Python
- Multiple Linear Regression
- Evaluation Metrics For Classification
- Machine Learning random forest algorithm
- Clustering algorithms in Machine Learning
- Clustering vs Classification
- Recommender system in Machine Learning
- Machine Learning Projects
- Decoding Model selection for Machine Learning
- Machine Learning Model Deployment using Flask
Technologies you'll Master
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Course Journey
Phase 1
Video Lectures & Live Classes
Dive into 100+ video lectures to build strong foundation starting from the very basics to advanced levels. 24/7 learning support from industry experts to clear up any conceptual doubts.Phase 2
Focus on projects
Capstone projects using real-world data sets with virtual labs for practical training.
Phase 3
Resume building, Mock interviews
Learn to make ATS-proof Latex Resume to get in eyes of the Recruiter easily. Get trained by experts, clear mock tests and Comp-coding rounds to get ready for Interviews.Phase 4
Internship & Placement
Get the required pre job experience to make your profile stand out. Make your dream of working in the tech company of your choices true with 100% assured placements.
Program outcomes
- In-depth knowledge in data analytics and data Visualisation..
- Good Command over Data Structure and algorithms, Machine learning,web scraping, and natural language processing..
- Mastery in essential concepts of data types, tuples, lists, dicts, basic operators, and functions..
- Hands on experience on Various live Projects..
- ATS Proof Latex Resume building and career-ready Skills..
- 100% Assured Internship and Placement..
Who will teach?
Jyoti Sharma
4.4 ReviewsOK Google Developer
B.Tech & M.Tech Computer Science at NIT Kurukshetra (Department Ranker 1, CGPA: 9.8) with experience in Android App Development and Machine Learning. I am highly enthusiastic about learning and teaching cutting-edge technologies. My interests include Teaching, Data Structures, Algorithms, and Problem Solving. Worked at Infoedge(Naukri), Ok Google, and got offers from various tech companies including Adobe, UrbanCompany, etc, I would love to create more developers by imparting what I know.
9 Topic
- Why Python
- Preparing your Machine (PC) for Python
- First Python Project & Assignment
- Constants, Reserved Words and Variables
- Module Assignment Solutions: Expressions and User
- Constants in Python: Introduction, application and use cases
- Variable Reserved Words in Python: Introduction, application and use cases
- Data Types in Python
- Conversions in Python: Type and string conversions
- Taking user inputs in Python: Introduction and application
- Module Quiz: Constant Resever Words Variables
- Constants Reserved Words Variables Assignment
- Module Assignment Solution: Expressions and User inputs
- Conditions And Comparisons: Introduction and Use Cases
- Functions and Code Reuse in Python
- Understanding Functions in Python
- Understanding Functions with Arguments in Python
- Return Functions: Introduction and use cases
- Multiple Arguments in Python: Introduction and use cases
- Module Quiz: Functions in Python
- Module Assignment: Functions in Python
- Module Assignment Solution: Functions in Python
- Loops and Iterations in Python
- Loops in Python: Introduction
- Break Continue: Understanding and Use Cases
- FOR Loop: Understanding and Use Cases
- Demo: Loops Code Implmentation
- Loops and interation
- Demo: Mastering Loops with more Use Cases
- Module Quiz: Loops in Python
- Module Assignment: Loops in Python
- Module Assignment Solution: Loops in Python
- BONUS VIDEOS
- Live Classes: Python
8 Topic
- Introduction to Strings and Functions
- Introduction Video: Data Structures Course Preview
- Introduction to Strings and LEN function Preview
- String Looping: Introduction and Use Cases
- String Slicing: Introduction and Use Cases
- String Library Function: Introduction and Use Cases
- Stripping Whitespace: Introduction and Use Cases
- Parsing Extracting
- Module Quiz: Strings in Python
- Module Assignment: Strings in Python
- Module Assignment Solution: Strings in Python
- Handling Files in Python
- Introduction to Files in Python
- Counting Lines in a File in Python: Introduction and use cases
- Reading files in Python: Introduction and use cases
- Searching Lines in a File in Python: Introduction and use cases
- Naming Files with User Data: Introduction and use cases
- Module Quiz: Files in Python
- Module Assignment: Handling files in Python
- Module Assignment Solution: Handling files in Python
- Lists in Python
- Introduction to Lists in Python
- Finding Length of Range Objects in Python: len()
- Continuation of lists and their use cases
- Calculating Sum and Average of Lists in Python
- Spliting Strings in to Lists in Python: split()
- Moduel Quiz: Lists
- Module Assignment: Lists in Python
- Module Assignment Solution: Lists in Python
- Dictionaries in Python
- Understanding Dictionaries in Python
- Distinguishing Lists and Dictionaries in Python: Lists Vs. Dictionaries
- Demo: Understanding Get Function in Python
- Iterating over dictionaries with loops
- Module Quiz: Dictionaries in Python
- Module Assignment: Dictionaries in Python
- Module Assignment Solution: Dictionaries in Python
- Tuples in Python
- Sets in Python
- Uderstanding Sets in Python
- Creating Sets in Python
- Creating Empty Dictionaries in Python: Empty Set
- Understanding Add and Update in Sets
- Deleting Elements of Sets in Python
- Distinguishing Sets, Lists and Dictionaries in Python: Sets Vs. Lists Vs. Dictionaries
- Python Set Operations (Union, Intersection, Difference and Symmetric Difference)
- Understanding Python Set Methods
- Module Quiz: Sets in Python
- Module Assignment: Python Sets
- BONUS VIDEOS
- Live Classes: Data Structures
6 Topic
- Object Oriented Programming: Introduction to OOPs
- Constructors in Python
- Encapsulation And Abstraction in Python
- Inheritance And Polymorphism in Python
- Module Quiz and Assignment
- Python Tutorials
- Python OOPs Concepts
- Python Seaborn Tutorial
- Sets in Python Tutorial
- H2O Tutorial : Machine Learning Framework
- Types of data distribution
- Erros in Machine Learning Models
- Dealing with Missing Values in Python
- Understanding Machine Learning: Use Case Scenarios
- Project: Medical Cost Prediction
- Python Libraries Guides
- Matplotlib: Creating Static, Animated, and Interactive visualizations in Python
- Pandas: Analysing Data in Python
- *Args And **Kwargs: Passing a variable number of arguments to a Python function
- NumPy: Working with Arrays in Python
- Red Wine Project
- Project - Stop Watch
13 Topic
- Machine Learning Introduction
- Regression in Python
- Introduction to Regression
- Various Regression Techniques: Linear, Polynomial, Stepwise, Ridge, Lasso and ElasticNet
- Linear Regression using Python
- Linear Regression Techniques: Slopes And Intercept
- Linear Regression using Sklearn Coding
- Linear Regression Demo using Scikit Lean Code Link
- Demo Code Explaination: Linear Regression using SKLEARN Coding
- Errors in Linear Techniques
- R-Squared or Coefficient of Determination
- Multiple Linear Regression (MLR)
- Polynomial Vs. Non Linear Regression
- Module Quiz: Regression in Python
- Machine Learning with Python: Classification
- Introduction to Classification
- K-Nearest Neighbor(KNN) Algorithm for Machine Learning Introduction
- Working with K-Nearest Neighbor(KNN) Algorithm for Machine Learning
- Evaluation Metrics for Classification
- Machine Learning Decision Tree Classification Algorithm
- Support Vector Machine (SVM) Algorithm in Machine Learning
- Machine Learning Random Forest Algorithm
- Module Quiz: Classification
- Clustering or Cluster Analysis in Machine Learning
- Recommender Systems in Machine Learning
- Python Project 1( Beginner Level): Building Your Own Guess Game
- Python Project 2 ( Intermediate Level): Playing with Graphs (Data Science Project)
- Python Project 3 (Advanced Level): Machine Learning (Deep Learning Project With Tensorflow)
- Live Class: Machine Learning
- Python Capstone Projects
- Machine Learning Workflow Optimization Techniques
- Understanding Machine Learning Workflow
- Decoding Model Selection for Machine Learning
- Understanding Overfitting in Machine Learning
- Understanding Underfitting in Machine Learning
- Understanding the Bias-Variance Tradeoff
- Introduction to Dimensionality Reduction for Machine Learning
- Gradient Descent algorithm and its Variants
- Machine Learning Model Deployment
- Developer Showcase: GitHub
1 Topic
- Building Professional Resumes
