Upcoming Batch !!!

Starting from July 15th, 2023

                     10:00 am – 2:00 pm


You Save Rs. 10000/-

  • 40 Hours Offline Classroom Sessions
  • 12Module 04 Projects 5 MCQ Test
  • 6 Months Complete Access
  • Access on Mobile and laptop
  • Certificate of completion
1250 Students Enrolled

Machine Learning

Machine learning is a branch of computer science that makes computers capable of learning without being openly programmed. ML is a subset of artificial intelligence (AI) that allows software applications to become more exclusive in calculating aftermaths. Machine Learning allows computers to learn from data and experiences, and make predictions or decisions based on that learning. According to the experts, Machine Learning and Artificial Intelligence will boom the digital industry by changing the methodology of how we interact with everything in our environment in the future.

Machine learning is used in various fields, such as image and speech recognition, natural language processing, recommendation systems, fraud detection, autonomous vehicles, and many others. It is a rapidly evolving field with constant research and development, aiming to create more accurate and efficient models to tackle complex problems across diverse industries.


What we will learn

Key characteristics of Machine Learning:

  1. Learning from Data: Machine learning algorithms learn from data, rather than being explicitly programmed. They can identify patterns and relationships in large datasets, making them capable of handling complex tasks.

  2. Adaptivity and Generalization: Once trained on a dataset, machine learning models can adapt to new, unseen data and make predictions or decisions on it. This ability to generalize to new data is a fundamental aspect of machine learning.

  3. Model Building and Training: The process of creating a machine learning model involves building a mathematical representation (algorithm) and training it on labeled data. During training, the model adjusts its internal parameters to improve its performance.

  4. Automation: Machine learning enables automation of decision-making processes by allowing algorithms to make predictions or decisions without human intervention. This automation can lead to increased efficiency and scalability in various applications.

  5. Iterative Improvement: Machine learning models can be refined and improved over time. By continuously feeding new data and updating algorithms, the models can enhance their performance.

  6. Non-linearity and Complexity Handling: Machine learning models can handle non-linear relationships and complex patterns in data, which traditional rule-based systems might struggle with.

  7. Probabilistic Outputs: Many machine learning algorithms provide probabilistic outputs, giving a measure of uncertainty for their predictions. This is particularly useful in decision-making under uncertainty.

  8. Feedback Loops: Machine learning models can receive feedback on their predictions and use it to refine their future predictions. This feedback loop allows the model to learn from its mistakes and improve its accuracy.

  9. Interdisciplinary Approach: Machine learning draws from various disciplines, including mathematics, statistics, computer science, and domain-specific knowledge. It often requires collaboration between experts from different fields to develop effective solutions.

  10. Diverse Applications: Machine learning has diverse applications across industries, including image and speech recognition, natural language processing, autonomous systems, recommendation systems, healthcare, finance, and more.

  11. Data-driven Decision Making: Machine learning facilitates data-driven decision-making by extracting insights and patterns from data that might be challenging or impossible for humans to discern.

Overall, Machine learning’s ability to learn from data, adapt, and make predictions autonomously has made it a transformative technology with widespread applications in the modern world.

Who can go for this

Everyone can take benefit’s from learnig Machine Learning:

Their is not a strict requirement while a background in computer science, mathematics, or statistics can be advantageous.

Course Content






40: Hrs

Introduction to Python Language, features, the advantages of Python over other programming languages, Python installation, Windows, Mac & Linux distribution for Anaconda Python, deploying Python IDE, basic Python commands, data types, variables, keywords and more.

Built-in data types in Python, tabs and spaces indentation, code comment Pound # character, variables and names, Python built-in data types, Numeric, int, float, complex, list tuple, set dict, containers, text sequence, exceptions, instances, classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug, basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise, loop and control statements, while, for, if, break, else, continue.

How to write OOP concepts program in Python, connecting to a database, classes and objects in Python, OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation, Python functions, return types, and parameters, Lambda expressions, connecting to database and pulling the data.

Understanding the Database, need of database, Installing MySQL on windows, showing databases available in MySQL Database Server, creating a Database in MySQl Workbench and showing it, understanding a MySQL Connector, understanding Database connection using Python.

Introduction to arrays and matrices, indexing of array, datatypes, broadcasting of array math, standard deviation, conditional probability, correlation and covariance.

Introduction to SciPy and its functions, building on top of NumPy, cluster, linalg, signal, optimize, integrate, sub packages, SciPy with Bayes Theorem.

How to plot graph and chart with Python, various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotLib, subplots.

Introduction to Python data frames, importing data from JSON, CSV, Excel, SQL database,

NumPy array to data frame, various data operations like selecting, filtering, sorting, viewing, joining, combining, how to handle missing values, time series analysis, linear regression.

Introduction to Exception Handling, scenarios in Exception Handling with its execution, Arithmetic exception, RAISE of Exception, what is Random List, running a Random list on Jupyter Notebook, Value Error in Exception Handling.


Introduction to Thread, need of threads, what are thread functions, performing various operations on thread like joining a thread, starting a thread, enumeration in a thread, creating a Multithread, finishing the multithreads. Understanding Race Condition, lock and Synchronization with lock.

Intro to modules in Python, need of modules, how to import modules in python, the import statement, locating a module, namespace and scoping, arithmetic operations on Modules using a function, Intro to Search path, Global and local functions, filter functions, Packages, Python Packages, import in packages, various ways of accessing the packages, Decorators, Pointer assignments, and Xldr.

Introduction to web scraping in Python, the various web scraping libraries, beautiful soup,

Scrapy Python packages, installing of beautiful soup, installing Python parser lxml, creating soup object with input HTML, searching of tree, full or partial parsing, output print, searching the tree.


Kushal Dwivedi

Hi I am Kushal Dwivedi and I am super excited that you are reading this.

Professionally, I am a data science management consultant with over 8+ years of experience in Banking, Capital Market, CCT, Media and other industry. I was trained by best analytics mentor at dunnhumby and now a days I leverage Data Science to drive business strategy, revamp customer experience and revolutionize existing operational processes.  

From this course you will get to know how I combine my working knowledge, experience and qualification background in computer science to deliver training step by step.  

Student feedback

4.5 OUT OF 5

Namita Nayak

1 year ago

It was a great experience of learning in palin analytics. The course content and the lecture delivery is quite good. It is totally hands-on learning and very satisfactory learning. The main thing I found in palin is, this organization is very supportive and you can reach out any time for your queries. I would like to reach out here for further courses and will recommend for a better learning place

Monojay Banerjee

1 year ago

One of the nice institutes in Delhi NCR, they do provide awesome training. I have seen in previous comments/reviews that Palin Institute do not provide demo classes but this is totally wrong they do send class recordings and as well as they ask you to attend a demo class as well to get a clear view on the classes.


Thank you Monojay…Best of Luck for your bright future.

Arju Khan

1 year ago

Took a weekend batch. The trainer is good . Has excellent knowledge of the concepts, liked his teaching style. Recommended.


Thanks Arju..

Add Reviews about your experience with us.


Countless Batch Access

Learn from anywhere

Industry Endorsed

Industry Expret Trainers

Industry Expret Trainers

Career Transition Guidance

Interview Preparation Techniques

Shareable Certificate

Real-Time Projects

Class recordings


Palin Analytics is ISO certified training institute is the best option to learn Python since we provide job-based training and our training curriculum is on par with industrial criteria.

Pool of working professionals with several years experience in same field with different domains like banking, healthcare, retail, ecommerce and many more. 

Along with the high quality training you will get a chance to work on real time projects as well, with a proven record of high placement support. We Provide one of the best Python Offline & Online Course, Training and Certification.

To avail of exciting offers and discounts on our Python training program, you can mail us at info@palin.co.in or call us a 9810600764. You can also visit our center to get your query resolved.

Its  Live interactive training, Ask your quesries on the go, no need to wait for doubt clearing.

you will have access to all the recordings, you can go through the recording as many times as you want.

Ask your questions on the go or you can post your question in group on facebook, our dedicated team will answer every query arises.

Yes we will help learners even after the subscription expires.

The duration of the Python course depends on the type of training mode you opt for, i.e., weekday batch, weekend batch, fast track batch, or online batch. For fee structure, you can visit our center or call us on 9810600764.

Python is one of the faster-growing languages that is easy to learn and easy to use. Also, 90 % of industries is using Python. This success also reveals a promising future scope of the Python programming language.


When you consider choosing the Python training course, you are likely to earn an attractive salary package as per your experience and knowledge. As you gain experience then you will earn to an unprecedented scale.

Becoming a Python programmer is very easy, there is no prior need of any programming knowledge, especially for those who have no experience of coding. By joining our Python Training, you can start learning the language.

Now these days Python is an additional subject included in Private schools. This training is suitable for freshers, graduates as well as postgraduates. If you are a professional who wants to polish your skills, then you can also attend this training.

No special requirements for learning Python. Anyone who has a passion to learn Python can join our training program.

  • Classroom Training
  • Online Training
  • One to One Live Training
  • Corporate Training
  • On-campus Training

We accept all the major payment modes like Cash, Card (Master, Visa, and Maestro, etc), Net Banking, UPI, Paytm, Google Pay, etc.

Yes, you’ll be given 100% placement assistance after the completion of the course.

Write Review

Lets us know your experience, it will help others.

Welcome Back, We Missed You!