Python with Data Science & Machine Learning (Duration : 8 Weeks)
All-Inclusive Coursework
In this course, you will learn the fundamentals of Python, from syntax to functions to data structures to files to modules and libraries to object-oriented programming.
Problem Solving:
Flask web development, Pandas data manipulation, and a lot more are all on the table.
Practical Exercises
Practical exercises are a major part of our curriculum. Throughout your course of study, you will engage in hands-on projects that serve to both solidify your knowledge and expand your resume. All the way from web app development to data analysis and robotic process automation, these initiatives cover it all.
Learning Through Interaction
In our method, hands-on experience is paramount. There are quizzes, coding exercises, and live coding challenges in our course. You’ll get immediate responses to your actions, letting you monitor your development and fine-tune your performance in real time.
Personalized Help from Educators
Our professional educators care deeply about your development. They are there to offer advice, clarification, and help anytime you require it. On the road to enlightenment, you will never be alone.
Comfort and adaptability
We recognize that students have varying availability. Our program is intended to be as accommodating as possible, so you may learn at your own speed and schedule.
Certification
After finishing the course and passing the accompanying exam, you will earn official recognition of your competence in Python. Having this credential on your resume will make you more marketable to prospective employers.
Who Should Sign Up for the NearLearn Python Programming?
Students of all experience levels and educational backgrounds are encouraged to enroll in our Python Programming Course.
- Novices
Python is a great language to learn for those who are just getting started in the field. Our course is organized to help you learn the basics and hone your programming skills over time.
- Skilled Programmers
Even seasoned programmers can learn something new from our training. Python’s flexibility makes it an indispensable tool for anyone working in fields as diverse as web development, data science, artificial intelligence engineering, and more.
- Learners and Job Seekers
Students interested in technical vocations and those seeking entry-level positions in the IT sector might give themselves an advantage by learning Python. It’s a highly sought-after expertise with significant value.
- Data Enthusiasts
Python is a great language to learn if you’re interested in data science and manipulation. To prepare you for data-driven careers, we cover fundamental data-related libraries like pandas and NumPy.
Reasons to Enroll in Our Python Training Course
You may be wondering what makes our course unique in light of the abundance of other available online materials. Here are some reasons why you should work with us:
- A Developed Course of Study
Our course is organized in a way that makes it easy to follow and covers all the bases. We help you build a strong foundation in Python by teaching you everything from scratch.
- Real-World Application
By applying what you learn to real-world situations, you’ll gain experience and confidence as you prepare for the workforce.
- Help for Teachers
All of our professional educators have a deep love of learning and a commitment to their students’ development. You can rely on their assistance at any point along the way.
- Adaptability
We understand that students have varying priorities and time commitments. You can take our course at your own pace and yet meet your other obligations, thanks to its adaptability.
- Validation
After finishing the course, you will be awarded a certificate that may be used to showcase your knowledge of Python to prospective employers.
- Social
When you enroll in our class, you join a group of people who are all committed to your success. You can improve your education by interacting with other students, hearing their perspectives, and working together on assignments.
Conclusion
If you’re interested in technology, data analysis, automation, and more, Python is so much more than just a programming language. To gain access to these possibilities and become an expert Python programmer, enroll in our Python Programming Course. This course is designed to give developers of all levels the tools they need to succeed in today’s high-tech environment. Don’t waste this opportunity to start learning to code and unlocking a world of possibility in your career. Get started with Python today by signing up for a course.
Course Schedule
Sample Certificates
IABAC Certificate
Course Video
Programming Languages & Tools Covered
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Testimonials
Manasa HG
Juniper Networks
“Nearlearn is one of the best institutes for Data science and Machine learning training in Bangalore. Training sessions were very interactive. Trainer has very good subject knowledge,I am very satisfied with both Trainer & Institute.”
Tushar Chorghe
GeBBS Healthcare Solutions
“I would rate services provided by NearLearn as excellent because of the instructor and venue with the required discount for the course. The overall experience was very good and will surely look forward to attend many more trainings”
Overview
- Be the first student
- Language: English
- Duration: 8 weeks
- Skill level: Any level
- Lectures: 108
- 3 Downloadable Resources
- 8 Сoding Exercises
- Certificate of Completion
Curriculum
- 10 Sections
- 108 Lessons
- 8 Weeks
- MACHINE LEARNING DATA SCIENCE AND THEIR IMPORTANCE9
- INTRODUCTION TO MACHINE LEARNING7
- 2.0What is Machine Learning (ML)?
- 2.1How machines learn
- 2.2Types of learning: Supervised, Semi-supervised, Unsupervised, Reinforcement.
- 2.3Basics of Classification, Regression and Clustering algorithms
- 2.4Creating your first Prediction Model
- 2.5Training & Model Evaluation
- 2.6Choosing Machine Learning Algorithm
- PYTHON LANGUAGE15
- 3.0Operators, Operands and Expressions
- 3.1Python Data Types
- 3.2Conditional statements in Python
- 3.3Loops in Python
- 3.4Lists and dictionaries and Tuples
- 3.5Programming practice in Python
- 3.6Iterators & Generators
- 3.7File Handling in Python
- 3.8Modules and Libraries
- 3.9Classes and Objects
- 3.10String Formatting in Python
- 3.11Decorators, Context Managers, Regular Expressions
- 3.12List and Dictionary Comprehensions
- 3.13Lambda and Argument Passing
- 3.14Multiple Inheritance
- PYTHON LANGUAGE11
- 4.0Introduction to Numpy
- 4.1Arrays, Matrices
- 4.2Various operations on arrays and matrices
- 4.3Introduction to Pandas
- 4.4Reading csv and matlab files
- 4.5Data frame object manipulation in python
- 4.6Various operations on data frame
- 4.7Visualization using Matplotlib
- 4.8Scatter plots, line plots etc on a given data
- 4.9Advance visualization using Seaborn
- 4.10Histograms, heatmaps, box plots etc using seaborn
- DATA PROCESSING FOR MACHINE LEARNING20
- 5.0Basic Functionalities of a data object
- 5.1Merging of Data objects
- 5.2Concatenation of data objects
- 5.3Types of Joins on data objects
- 5.4Exploring a Dataset
- 5.5Analysing a dataset
- 5.6Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples() operations
- 5.7Aggregation
- 5.8Concatenation
- 5.9Merging
- 5.10Joining
- 5.11Data Collection &Preparation
- 5.12Data Mugging
- 5.13Outlier Analysis
- 5.14Missing value treatment
- 5.15Feature Engineering
- 5.16Data Transformation
- 5.17Normalization vs Standardization
- 5.18Creating Dummies
- 5.19Principal Component Analysis
- STATISTICS FOR MACHINE LEARNING AND DATA SCIENCE12
- REGRESSION MODELLING6
- ADVANCED MACHINE LEARNING ALGORITHMS12
- 8.0Supervised Machine Learning algorithms
- 8.1Linear Regression o Multi Feature
- 8.2Logistic Regression
- 8.32 Class and Multi class
- 8.4Decision/ Classification Trees Ensemble Models Bagging Boosting Random Forest
- 8.5K-Nearest Neighbours (KNN)
- 8.6Naive Bayes
- 8.7Introduction to Neural Network (DeepLearning)
- 8.8Feed Forward Neural Network
- 8.9Forward Propagation
- 8.10Backward Propagation
- 8.11Support Vector Machine
- Unsupervised Machine Learning algorithms4
- FEW SAMPLE CASE STUDY AND PROJECTS12
- 10.05000+ Handwritten Digit Recognition Problem
- 10.14000+ email spam detection problem
- 10.2Image compression Problem
- 10.3Flower species classification problem
- 10.4Titanic Survivor classification problem from kaggle
- 10.5Fifa ranking dataset from kaggle
- 10.6Profit Prediction Problem
- 10.7Business Case of whether a chip will be accepted or not
- 10.8Business case of clustering from dataset
- 10.9Wine classification dataset and problem from Kaggle
- 10.10Variety of Problems from Kaggle
- 10.11Competition Data Set
