Python Training and Certification for Data Science and Analytics

  • Course Duration135 Hrs.
  • Course ModeInstructor Led Training
  • Course Fee₹ 7200

About The Course

Data Science and Analysis comes into the frame with huge data collections and large numbers of machine learning applications development around the globe. This course will deal with extracting meaning insights from huge set of labelled or unlabelled data through the process of Data cleaning, analysis and pre-processing. We will learn around the packages, syntax and commands of Python. Various Machine learning advancement based out of data science such as Supervised and Unsupervised Learning will be discussed and figured out to understand real time implementations. You can join our batches starting in every 15 days

Key Features

Instructor–led training

Highly interactive instructor-led training

Free lifetime access to recorded classes

Get lifetime access of all recored classes in your profile

Regular assignment and assessments

Real-time projects after every module

Lifetime accessibility

Lifetime access and free upgrade to the latest version

3 Years of technical support

Lifetime 24/7 technical support and query resolution

Globally Recognized Certification

Get global industry-recognized certifications


•    You will be able work upon some real time data sets for analytical and information extraction problem statements.
•    You will develop understanding about all those industries which are really relying upon data and data science means a lot to them.
•    All the concepts that are required and based out of data sets for a machine learning problem solving will be discussed by industry specialists.
•    Any set of complex problem will be breached up into simplest solvable parts

Mode of Learning and Duration

  • Weekdays – 15 to 16 weeks
  • Weekend – 17 to 18 weeks
  • FastTrack – 10 to 12 weeks
  • Weekdays – 15 to 16 weeks
  • Weekend – 17 to 18 weeks
  • FastTrack – 10 to 12 weeks


Course Agenda

  • What is Data Science and what does a data scientist do.
  • Various examples of Data Science in the industries and how Python is deployed for
  • Data Science applications
  • Various steps in Data Science process like data wrangling, data exploration
  • selecting the model
  • What is exploratory data analysis and building of hypothesis, plotting and other techniques.
  • Introduction to Python
  • Introduction to Python programming language
  • Important Python features, how is Python different from other programming languages
  • Python installation
  • Anaconda Python distribution for Windows, Linux and Mac
  • How to run a sample Python script
  • Python IDE working mechanism
  • Running some Python basic commands, Python variables, data types and keywords.
  • Introduction to a basic construct in Python
  • Understanding indentation like tabs and spaces
  • Code comments like Pound # character, names and variables
  • Python built-in data types like containers (list, set, tuple and dict), numeric (float, complex, int), text sequence (string), constants (true, false, ellipsis) and others (classes, instances, modules, exceptions and more)
  • Basic operators in Python like logical, bitwise, assignment, comparison and more, slicing and the slice operator
  • Loop and control statements like break, if, for, continue, else, range() and more.
  • Understanding the OOP paradigm like encapsulation, inheritance, polymorphism and abstraction
  • What are access modifiers, instances, class members, classes and objects
  • Function parameter and return type functions
  • Lambda expressions, connecting with database to pull the data.
  • Introduction to mathematical computing in Python
  • What are arrays and matrices, array indexing, array math, ND-array object
  • Data types, standard deviation
  • Conditional probability in NumPy, correlation, covariance SciPy for Scientific Computing
  • Introduction to SciPy
  • Building on top of NumPy
  • What are the characteristics of SciPy
  • Various sub packages for SciPy like Signal, Integrate, Fftpack, Cluster, Optimize, Stats and more
  • Bayes Theorem with SciPy
  • Introduction to Machine Learning with Python
  • Various tools in Python used for Machine Learning like NumPy, ScikitLearn, Pandas, Matplotlib and more
  • Use cases of Machine Learning
  • Process flow of Machine Learning and Various categories of Machine Learning
  • Understanding Linear Regression and Logistic Regression
  • What is gradient descent in Machine Learning
  • Introduction to Python DataFrames, importing data from JSON, CSV, Excel, SQL database, NumPy array to DataFrame
  • Various data operations like selecting, filtering, sorting, viewing, joining and combining, how to handle
  • missing values, time series analysis
  • What is a data object and its basic functionalities?
  • Using Pandas library for data manipulation
  • NumPy dependency of Pandas library, loading and handling data with Pandas
  • How to merge data objects, concatenation and various types of joins on data objects
  • Exploring and analyzing datasets
  • Data Visualization with Matplotlib
  • Using Matplotlib for plotting graphs and charts like Scatter, Bar, Pie, Line, Histogram and more
  • Matplotlib API, Subplots and Pandas built-in data visualization
  • What is supervised learning, classification
  • Decision Tree, algorithm for Decision Tree induction
  • Confusion Matrix
  • Random Forest
  • Naïve Bayes, working of Naïve Bayes, how to implement Naïve Bayes Classifier
  • Support Vector Machine, working process of Support Vector Mechanism
  • What is Hyper Parameter Optimization
  • Comparing Random Search with Grid Search
  • How to implement Support Vector Machine for classification?
  • Introduction to unsupervised learning, use cases of unsupervised learning
  • What is K-means clustering, understanding the K-means clustering algorithm
  • Optimal clustering
  • Hierarchical clustering and K-means clustering and how does hierarchical clustering work
  • What is natural language processing, working with NLP on text data
  • Setting up the environment using Jupyter Notebook
  • Analyzing sentence, the Scikit-Learn Machine Learning algorithms Bags of words model
  • Extracting feature from text
  • Searching a grid, model training, multiple parameters and building of a pipeline
  • Introduction to Text Mining
  • Introduction to Sentiment
  • Setting up API Bridge, between Python and Twitter Account
  • Extracting Tweet from Twitter Account
  • Scoring the tweet
  • What is Time Series data?
  • Time Series variables
  • Different components of Time Series data
  • Visualize the data to identify Time Series Components
  • Implement ARIMA model for forecasting
  • Exponential smoothing models
  • Identifying different time series scenario based on which different Exponential Smoothing model can be applied
  • Implement respective ETS model for forecasting
  • Introduction to web scraping in Python, various web scraping libraries
  • BeautifulSoup, ScrapyPython packages
  • Installing of BeautifulSoup
  • Installing Python parser lxml
  • Creating soup object with input HTML
  • Searching of tree, full or partial parsing, output print and searching the tree
  • What is the need for integrating Python with Hadoopand Spark
  • The basics of the Hadoopecosystem, Hadoop Common
  • The architecture of MapReduce and HDFS and deploying Python coding for MapReduce jobs on Hadoop framework
  • Understanding Apache Spark
  • Setting up Cloudera QuickStart VM
  • Spark tools
  • RDD in Spark
  • PySpark, integrating PySpark with Jupyter Notebook
  • Introduction to Artificial Intelligence and Deep Learning
  • Deploying Spark code with Python
  • The Machine Learning library of Spark Mllib
  • Deploying Spark MLlib for classification, clustering and regression parameters and building of a Pipeline



Industry: - Entertainment

Problem Statement: - An online video streaming company wants to know about viewing pattern of its subscriber and build a recommendation system for better viewing experience.

Description: - This real time project will give you a hands-on experience with a movie recommendation system based on which type of movie liked by a user and other viewing choices. You can build a data-driven recommendations. It involves information filtering, rating predictions, learning user preferences and so on. You will work with movie related data contains user details, movie details and others.

Industry: - E-commerce, Research, Lead Generation

Problem Statement: - You need to scrap large amount of meaning full information from the data available over the web.

Description: - You will lead to understand web scrapping using python which involves installation of beautiful soup, libraries, working on targeted data and different web page formats. Important aspects that a learner will understand different possible kinds of objects, string navigations, searching tree deployment, various navigation options such as searching by CSS class, list, functions and keyword arguments.

Industry: - Bank and Finance

Problem Statement: - A major financial Intuition decided to use its data source to detect any possible fraudulent activity and take remedial measures to avoid it.

Description: - With this real time project you will work with some banking transactional data, finding out outliers in the data and classify it based on various parameters. Different statistical techniques will be applied to look for any possible fraudulent activity in the transactional system.

Industry: - e-commerce

Problem Statement: - An e-commerce company wants to know how to deploy targeted selling to its customers

Description: - This is a data science and analysis project to understand once buying habit and sell the product that suits them. The process starts with buying and selling data pre-processing which includes aggregation, cleaning, transforming and collecting consumer buying history to deploy statistical analysis, predictive modelling, and profile creations of consumers to implement more targeted selling.



Career Support

We have a dedicated team which is taking care of our learners learning objectives.


There is no such prerequisite if you are enrolling for Master’s Course as everything will start from scratch. Whether you are a working IT professional or a fresher you will find a course well planned and designed to incorporate trainee from various professional backgrounds.

AI Council offers 24/7 query resolution, you can raise a ticket with a dedicated support team and expect a revert within 24 Hrs. Email support can resolve all your query but if still it wasn’t resolved then we can schedule one-on-one session with our instructor or dedicated team. You can even contact our support after completing the training as well. There are no limits on number of tickets raised.
AI council provide two different modes for training one can choose for instructor lead training or learning with prerecorded video on demand. We also offer faculty development programs for college and schools. apart from this corporate training for organization/companies to enhance and update technical skills of the employees. We have highly qualified trainers who are working in the training industry from a very long time and have delivered the sessions and training for top colleges/schools and companies.
We are providing a 24/7 assistance for the ease of the student. Any query can be raised through the interface itself as well as can be communicated through email also. If someone is facing difficulties with above methods mentioned above we can arrange a one on one session with the trainer to help you with difficulties faced in learning. You can raise the query throughout the total training period as well as after the completion of the training.
AI Council offers you the latest, appropriate and most importantly the real-world projects throughout your training period. This makes student to gain industry level experience and converting the learning’s into solution to create the projects. Each Training Module is having Task or projects designed for the students so that you can evaluate your learning’s. You will be working on projects related to different industries such as marketing, e-commerce, automation, sales etc.
Yes, we do provide the job assistance so that a learner can apply for a job directly after the completion of the training. We have tied-ups with companies so when required we refers our students to those companies for interviews. Our team will help you to build a good resume and will trained you for your job interview.
After the successful completion of the training program and the submission of assignments/quiz, projects you have to secure at least B grade in qualifying exam, AI Council certified certificate will be awarded to you. Every certificate will be having a unique number through which same can be verified on our site.
To be very professional and transparent No, we don’t guarantee the job. the job assistance will help to provide you an opportunity to grab a dream job. The selection totally depends upon the performance of the candidate in the interview and the demand of the recruiter.
Our most of the programs are having both the modes of training i.e. instructor led and self-paced. One can choose any of the modes depending upon their work schedule. We provide flexibility to choose the type of training modes. While registering for courses you will be asked to submit your preference to select any of the modes. If any of the course is not offered in both modes so you can check in which mode, the training is going on and then you can register for the same. In any case if you feel you need any other training mode you can contact our team.
Yes, definitely you can opt for multiple courses at a time. We provide flexible timings. If you are having a desire for learning different topics while continuing with your daily hectic schedule our course timing and modes will help you a lot to carry on the learning’s.
Whenever you are enrolling in any of the courses we will send the notification you on your contact details. You will be provided with unique registration id and after successful enrollment all of the courses will be added to your account profile on our website.AI Council provides lifetime access to course content whenever needed.
A Capstone project is an outcome of the culminating learning throughout the academic years. It is the final project that represents your knowledge, efforts in the field of educational learning. It can be chosen by the mentor or by the students to come with a solution.
Yes, for obtaining the certificate of diploma programmer you have to submit the capstone project.