This is a foundation course for every technical professional aspiring to become a machine learning engineer. The course offers a unique combination of python programming and statisitcs. This course is tailored for students and professionals from non-it field.



Instructor-led live classes with access to recordings of the classes

Taught from scratch: no prior knowledge of programming is required.

Course covers Algorithms, Data Structures and Object Oriented Programming

Languages and Tools covered

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About the



Python programming is a must in the present IT industry. Python is used extensively in the Industry for vast number of automation and software development activities. Python is the first language of choice for Machine Learning and AI. Certisured presents a complete python programming course which starts from the fundamental concepts of binary , and scale it to object oriented programming in Python.

This course will be taught in two phases. Phase one spans for 40 Days and will consists on hands on Python programming . Phase two will span for 20 days and will deal with only practical projects mentored by instructors.

Who should apply for this course?

  • Professionals from It-domain who want to master programming python.
  • Students from Non-IT domain who want to master Industry level programming
  • Professionals from non-it domain looking for transitioning into machine learning , AI and Data science/Analytics


This course will be held online on Discord


This course is scheduled to start from September 10th 2021.


2 months of online training.



  • Certisured certification is an earned certificate. As a policy, our assessments are hard and the KPI's to full-fill are on par with industry standards. A student can take as much time as they want, and ask for as many explanations as they wish, but the required assignments and submissions must be submitted with industry standards set by the instructor.
  • Certisured is the India’s first Ed-Tech platform where courses and LMS are designed to include scheduled audio/video summary of lesson on the 1st, 3rd and 7th day to enable long term retention of concepts.
  • Certisured aims at creating maximum opportunities for our students, helping them to stand out from the crowd. Your success is finally our success.
  • Certisured aims to ensure that each student is skilled enough to greatly excel in his or her professional career.


This course is a detailed industry excellence program. If you want just theoretical lessons without practical implementation , then this course is not for you. Instead, if you want to learn exactly how things are done in the industry and want to make a career as a Python developer leading to a future in machine learning engineer, then you are in the right place.

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Module 1: Introduction to Computation

This section covers the fundamental aspects of how computers actually compute. The student will get a clear understanding of how computing machines were built from scratch and how hardware and software have both evolved with time.

Binary Numbers and Electronic Memory

This section introduces the fundamental concepts of what a binary number is and how its is represented inside the computer as a bit. Using this as the starting point, the concepts of higher abstractions of bytes and memory are connected. This section is a must for attain a strong foothold and confidence in knowing different kinds of errors that occur during coding.

  1. Understanding the computer architecture.
  2. The Arithmetic and Logical Unit
  3. Computer processors, clocks and machine code

The architecture of a computer is a hardware made of electronic components. The automation of the same is achieved by a piece of software which regulates and monitors the flow of information according to a standard operating procedure. In this section we will understand the layers of operating systems in the context of general architecture of the underlying hardware.

Data structures are the fundamental units for packing information. Data structures are common for all programming languages. Students will learn to appreciate the need for every standard structure of data such as bit, byte, arrays, lists, pointers, references, stacks, structures, dictionary, tuple and advanced Data Structures such as Linked-List, Stacks, Queues and Trees.

An Algorithm is a set of operations that is designed to get some task done. In the context of computation, the tasks are based on information flow, information manipulation and often, the task are designed in such a way that the computer will do certain tasks repeatedly to achieve the desired output. This section although is a part of advanced computation, will add to a broader understanding of how to write efficient programs and why certain kids of data structures are chosen above other structures to achieve faster and efficient outputs.

Time complexity and Space complexity will be understood in detail, making the student aware of practical issues which they might face in their professional careers as software developers.

Here will understand what a computer program actually does. How it communicates and interacts with the hardware. We will further build on this knowledge and realize the difference between different kinds of computer programming languages and why they are different in nature. This knowledge is important for every software developer for a confident approach to choosing a language for automation.

The OOP language enables the program to be broken down into smaller programs that can be readily solved (one object at a time). The new technology promises increased programmer efficiency, higher software quality, and lower maintenance costs. From smaller to big systems, OOP systems can be readily scaled. In this section we will understand the fundamental concepts of how a object is defined out of class and build the intuition to appreciate advanced concepts in object oriented programming.

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Module 2: Hand's On Python Programming

In this section we will begin with actual python coding. The student will get complete hand holding step by step as we understand that the initial phases of programming is a hard phase and with a lot of confusions. So the student will be guided through out until they start executing programs successfully.

Python Setup

In this section, student will be guided with installation of basic laboratory and the required software which will be used in the initial phase of coding. Student will understand the basic IDE setup and other sub modules which will be used along the course.

Python is around from 20+ years and enjoy tremendous support from developers community. Python also has a very strong documentation available online. Students will be introduced to different platforms where answers to almost every error is found. It is believed that finding answers online is also a key technical skill of a developer.

Python's core data structures are list, set, tuples, and dictionary. Each data structure is distinct in its own manner. Data structures are "containers" that organize and categorize data. The mutability and order of the data structures varies.

  1. Lists
  2. Arrays
  3. Tuple
  4. Dictionary
  1. Arithmetic operations in Python
  2. Comparison Operators in Python
  3. Boolean operators
  4. Python Statements
  1. How to define a function
  2. How to pass function as an argument
  3. Defining a Python class and object.
  4. Hands-On exercise

Loops are useful in Python and other programming languages because they allow you to execute a block of code repeatedly. You will frequently encounter circumstances in which you will need to utilize a piece of code again but do not want to write the same line of code numerous times.

  1. While loop
  2. For loop
  3. Nested loops
  4. Difference between using a while loop and a for loop.
  5. Using the break and continue keywords.
  6. The difference between the xrange() and range() functions

Errors are issues in a program that cause the program to cease running. Exceptions, on the other hand, are raised when some internal events occur that disrupt the usual flow of the program.

Python has two sorts of errors.

  1. Syntax errors
  2. Logical errors (Exceptions)
  1. Decorators
  2. Generators
  3. Generator expressions
  4. Iterators
  5. Closures
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Module 3: Advanced Python Programming

In this module we will explore python language for different activities generally used in automation of tasks such as web scrapping, email automation, reading word, pdf and excel sheets through a python code.

File reading

Reading a file is a fundamental aspect of coding. In this section we will learn how to read Excel sheets/ CSV files , PDFs & Spreadsheet, with Python

Assume you need to retrieve a huge amount of data from a website and you need to do it as soon as feasible. How would you do it if you didn't go to each website and personally collect the data? Web scraping is the solution. In this era where data is money, web scrapping is employed all over the companies to collect and further, this data is mined using natural language processing. In this section we will be learning some cool web scrapping techniques which will be handy for you in your python coding career.

Image processing with Python begins with manipulating images using PIL. PIL stands for Python Imaging Library, and it offers image editing capabilities to the Python interpreter. It was created by Fredrik Lundh and numerous other people. Pillow is a easy-to-use PIL fork and a handy library. We'll be collaborating with Pillow to do the following:

  1. Open a particular image from a path
  2. Retrieve size of image
  3. Save changes in image
  4. Image Rotating, Cropping, & Resizing
  5. Pasting an image on another image
  6. Getting a Histogram of an Image
  7. Transposing an Image
  8. Splitting an image into individual bands
  9. Converting an image to an X11 bitmap (A plain text binary image format) using "tobitmap"
  10. Creating a thumbnail
  11. Get emotions of images using Microsoft emotion API in Python

Receive and send personalized emails and set up an automated system.

  1. Why email automation?
  2. Getting Started
    • Option 1: Setting up a Gmail Account for Development
    • Option 2: Setting up a Local SMTP Server
  3. Sending a Plain-Text Email
    • Starting a Secure SMTP Connection
    • Sending Your Plain-text Email
  4. Sending Fancy Emails
    • Including HTML Content
    • Adding Attachments Using the email Package
  5. Sending Multiple Personalized Emails
  • Make a CSV File With Relevant Personal Info
  • Loop Over Rows to Send Multiple Emails
  • Personalized Content
  • Code Example

Graphical user interface (GUI) is often seen as a last phase of software development. Once your python code is ready for deployment, the developer has to cater to the fact that the user of this code will not always key in the inputs through the raw code. A GUI helps in creating the interface between the User and the raw code.

PySimpleGUI: The Simple Way to Create a GUI With Python

  1. Introduction to PySimpleGUI
  2. Installing PySimpleGUI
  3. Creating Basic UI Elements in PySimpleGUI
  4. Creating Simple Applications
  5. Creating a PySimpleGUI Image Viewer
  6. Integrating Matplotlib With PySimpleGUI
  7. Integrating OpenCV With PySimpleGUI
  8. Packaging Your PySimpleGUI Application for Windows
  9. Conclusion
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Module 4: Python for Data Science

This section delves into using python programming language as a language to automate data driven decision making. We start with understanding the basic modules and delve deeper into the details of each module.

Introduction to Numpy

NumPy is one of the fundamental packages in Python

NumPy is a Python-based array-processing library. It provides high-performance, multidimensional array objects as well as array-related utilities. NumPy is a useful container for general multidimensional data.

The fundamental object of NumPy is the homogeneous multidimensional array.

It is a table of the same datatype elements or numbers, indexed by a tuple of positive integers. Dimensions are referred to as axes in NumPy, and the number of axes is referred to as rank. The array class in NumPy is known as ndarray aka array.

When should you utilize it?

NumPy is used to work with arrays that contain values of the same datatype. NumPy simplifies array math operations and vectorization. . This significantly enhances performance and speeds up the execution time correspondingly.

What can you do with NumPy?

  • Basic array operations: add, multiply, slice, flatten, reshape, index arrays
  • Advanced array operations: stack arrays, split into sections, broadcast arrays
  • Work with DateTime or Linear Algebra
  • Basic Slicing and Advanced Indexing in NumPy Python

Matplotlib is an excellent Python visualization toolkit for 2D array charts. Matplotlib is a multi-platform data visualization toolkit based on NumPy arrays and designed to interact with the wider SciPy stack. John Hunter first used it in 2002.

One of the most important advantages of visualization is that it provides us with visual access to massive volumes of data in readily consumable images. Matplotlib has a variety of plots such as line, bar, scatter, histogram, and others.

  1. Installation
  2. Importing matplotlib
  3. Basic plots in matplotlib
  4. Line plot
  5. Bar plot
  6. Histogram
  7. Scatter Plot
  8. Violin plot in Python using axes class of Matplotlib

Seaborn is a Python module that is primarily used for statistical charting. It is built on Matplotlib and has stunning default styles and color palettes to make statistics graphs more visually appealing.

In this section, we will study Python-Seaborn from the ground up, utilizing a massive dataset containing seaborn basics, ideas, and graphs that may be displayed.

  1. Getting Started

  2. Using Seaborn with Matplotlib

  3. Customizing Seaborn Plots

    • Changing Figure Aesthetic
    • Removal of Spines
    • Changing the figure Size
    • Scaling the plots
    • Setting the Style Temporarily
  4. Color Palette

    • Diverging Color Palette
    • Sequential Color Palette
    • Setting the default Color Palette
  5. Multiple plots with Seaborn.

    • Using Matplotlib

    • Using Seaborn

    • Creating Different Types of Plots

    • Relational Plots

    • Categorical Plots

    • Distribution Plots

    • Regression Plots

  1. Introduction

    • Introduction to Pandas
    • How to Install Python Pandas
  2. Creating Objects

    • Pandas DataFrame
    • Creating a Pandas DataFrame
    • Pandas Series
      • Creating a Pandas Series
  3. Viewing Data

    • View the top rows of the DataFrame
    • View the bottom rows of the DataFrame
    • View basic statistical details
    • Convert the pandas DataFrame into a numpy Array
    • Convert the pandas Series into a numpy Array
    • Convert series or dataframe object to Numpy-array using .as_matrix().
  4. Selection

    • Dealing with Rows and Columns in Pandas DataFrame
    • How to select multiple columns in a pandas dataframe
    • Python | Pandas Extracting rows using .loc[]
    • Python | Extracting rows using Pandas .iloc[]
    • Indexing and Selecting Data with Pandas
    • Boolean Indexing in Pandas
    • Label and Integer based slicing technique using DataFrame.ix[ ]
  5. Manipulating Data

    • Adding new column to existing DataFrame in Pandas
    • Python | Delete rows/columns from DataFrame
    • Truncate a DataFrame before and after some index value
    • Truncate a Series before and after some index value
    • Iterating over rows and columns in Pandas DataFrame
    • Working with Missing Data in Pandas
    • Sorts a data frame in Pandas | Set-1
    • Sorts a data frame in Pandas | Set-2
  1. Grouping Data

    1. Pandas GroupBy
    2. Grouping Rows in pandas
    3. Combining multiple columns in Pandas groupby with dictionary
  2. Merging, Joining and Concatenating

    1. Python | Pandas Merging, Joining, and Concatenating
    2. Concatenate Strings
    3. Append rows to Dataframe
    4. Concatenate two or more series
    5. Append a single or a collection of indices
    6. Combine two series into one
    7. Add a row at top in pandas DataFrame
    8. Join all elements in list present in a series
    9. Join two text columns into a single column in Pandas
  3. Working with Date and Time

    1. Python | Working with date and time using Pandas
    2. Timestamp using Pandas
    3. Current Time using Pandas
    4. Convert timestamp to ISO Format
    5. Get datetime object using Pandas
    6. Replace the member values of the given Timestamp
    7. Convert string Date time into Python Date time object using Pandas
    8. Get a fixed frequency DatetimeIndex using Pandas
  4. Working With Text Data

    1. Python | Pandas Working With Text Data
    2. Convert String into lower, upper or camel case
    3. Replace Text Value
    4. Replace Text Value using series.replace()
    5. Removing Whitespaces
    6. Move dates forward a given number of valid dates using Pandas
  5. Working with CSV and Excel files

    1. Read csv using pandas
    2. Saving a Pandas Dataframe as a CSV
    3. Loading Excel spreadsheet as pandas DataFrame
    4. Creating a dataframe using Excel files
    5. Working with Pandas and XlsxWriter | Set – 1
    6. Working with Pandas and XlsxWriter | Set – 2
    7. Working with Pandas and XlsxWriter | Set – 3
  6. Visualization

    1. Pandas Built-in Data Visualization
    2. Data analysis and Visualization with Python | Set 1
    3. Data analysis and Visualization with Python | Set 2
    4. Box plot visualization with Pandas and Seaborn
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Module 5: SQL Programming for Data Science

Businesses and sectors are gathering and churning out billions of data points every day, thanks to the huge amounts of data that are now available. To make sense of the big data phenomena — whether in the medical sector, education, business, sports, or elsewhere — an appropriate skill set is required.

These businesses must be able to gather and retain data as well as analyze it in order to make strategic and informed decisions that will enhance their profitability and solve real-world problems. Consider being able to use big data to create a model that will alleviate traffic and make transportation in large cities simple and comfortable.

This and many more things are possible, and SQL is one of the talents required of a data scientist.

Introduction to Structured Query Language ( SQL )

  1. Introduction to Data bases
  2. Difference between SQL and No-SQL data bases
  3. Understanding a query
  4. Overview of what will be learnt in this module
  1. Downloading the data that will be used in this module
  2. Understanding MS SQL Management Studio
  3. Uploading data and related short-cuts
  1. Using SELECT statement to select data
  2. Using WHERE statement to filter data
  3. Using Wildcards/Regular expressions to SQL for advanced filtering and pre-processed filtering
  4. Comments in SQL
  5. Order By
  6. Data Types in SQL
  7. Implicit Data Conversion in SQL
  8. Using Cast() vs Convert()
  9. Working with NULLs
  10. Understanding how LEFT, RIGHT, INNER, and OUTER joins work
  11. Joins with duplicate values
  12. Joining on multiple fields
  13. Practicing Joins
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Bonus Topic

This course is a foundation course for Machine learning and AI. We will finish this course with an introduction to machine learning and what value it holds in shaping the future of the world.

Introducion to Machine Learning

  • How machines learn
  • Types of machine learning
  • Types of machine learning jobs and their salary packages
  • How to plan a career in Machine Learning, Artificial Intelligence and Data science
  • Further resources, books and materials which will add value to your quest!
What our

students say

Certisured conducted a workshop on emerging technologies at MIT. Our students were thoroughly enlightened by the knowledge imparted. We got a very good feedback from students.

Dr C Gurudas Nayak

Professor at MIT MAHE Manipal

Mr Vijay Shanthagiri from Certisured gave a very detailed over view of how AI is used for Battery Technology . The Engagement was immersive leading to many future collaborations.

Dr Ravi Kumar Gupta

Associate Professor at Manipal University Jaipur

video reviews


Data Analyst


Machine Learning Engineer

Workshops across india

Manipal University

Asked Question

Some of the frequently asked questions about the course are answered here


Who should apply for this course and what should be the study path?

This course is structured for those who are interested mastering programming. The course begins with a strong introduction to the world of computing, followed by introduction to Operating systems, Data Structures and Algorithms. The student will also learn the fundamental concepts which will make them see programming languages differently. This course is a live instructor led class where students are mentored to become coders and think like developers.


Should I know programming to excel in this course?

No, we don't assume any prior programming knowledge. Instead this course is for those who do not have any prior knowledge of programming. Python programming will be taught in depth as a part of this course. This course will be very practical and the only thing expected of student is a strong desire to learn coding. If the student is motivated and does all the assignments well, then success is assured.


Where will the course be conducted?

We provide online as well as offline modes of training. Our live online training on the discord platform will provide you with the same learning experience you would receive in a physical classroom, without the hassle and cost of travel. You will interact with the instructor the same way you would in a physical course and receive the same course-ware, labs, and tools. Our online programs are as interactive as the physical classroom. Try our online demo class to see it for real!


Will you provide a certificate?

We will provide two certificates namely, certificate for training and certificate of merit. We also provide a mark sheet which consists of detailed assessment of the students. Our certificate is accepted globally and many of our students are placed world-wide.


Will I get a coding job after attending this course?

This course is designed to pave a very strong foundation for a coding career related to machine learning and data science. Since we are covering all the aspects of computing and python programming, any student who completes the course with all the assignments and assessments, will crack any python interview and excel in their career as coders.


Do you provide Job assistance?

We provide 100% job assistance. Our program is designed in such a way that we groom you to become industry-ready with Certisured’s unique placement program. We make sure that our students are well placed and industry ready in all the aspects which includes resume preparation, video resume, linked profile optimization, portfolio creation, blogs by students, and a certification which has high value in the industry.


Pricing & Discounts

Early bird entries will get a discount up to 20% on the standard package. The batch is schedule to start from September 10th 2021. The coupon codes are valid till September 7th. So register before September 7th and redeem your coupons.

For Indian Students

Use the appropriate coupon codes to get 20% off. If you wish to get a coupon code, you will have to attend the demo class. Register for the same below.

Starts at


Extra benefits !
  • Complete course and mentorship
  • 10 hands on projects
  • Assistance with Portfolio, Resume and Placement
  • Mock Interview Preparation

For International Students

Use the appropriate coupon codes to get 20% off. If you wish to get a coupon code, you will have to attend the demo class. Register for the same below.

Starts at

US$ 200.

Extra benefits !
  • Complete course and mentorship
  • 10 hands on projects
  • Assistance with Portfolio, Resume and Placement
  • Mock Interview Preparation

Register for the demo class

If you want to know more details or talk to the instructor , register below for the demo class. Those who attend the demo class will get a coupon code too !