This course will help you to learn Python for Data Analysis

Dear Participant,

SaNDS LabTM  academic division Executive Education welcomes you to the world of real-time Interactive Live Session (ILS) through its pioneering efforts.

We would like to congratulate you on having made such a prestigious programme. We also wish that your experience be one of significant enrichment & immense help in substantially building your career growth.

This “Participant Manual” is designed to help you through the programme delivery. We have a team of programme support who shall be your escalation contact in case of any issues or help that you may seek.

You may write to us at

We may add that we are indeed using state of the art technology. However, like any other technology, it is prone to fail, As per the prevailing infrastructure in India, the intermittent drops in the network connectivity or packet loss are unavoidable. Hence you might face audio or video issues if the internet quality or bandwidth is not optimal.

We will keep you updated regularly on the various other initiatives from our end and shall seek your co-operation to make your experience a most memorable one.


 Wishing you all the very best in your career and happy learning, Sincerely,


Programme Support Team



1.       Records

It’s the responsibility of the participant to keep the personal records like e-mail id, mobile numbers, residence address, communication address, etc.

Correct and update in the application form. In Record, if found incorrect or fake, the candidature of the participant shall stand cancelled.

Your Records will be used simultaneously by SaNDS LabTM  academic division, the former being used for various commercial/fee purposes & the latter for all academic interactions. Accuracy of participant detail in the systems is entirely a participant’s responsibility, and SaNDS LabTM  academic division shall not take cognizance of any error that is caused by incorrect data.

A participant is not allowed to change his/her name at any stage after the conformation. A participant is strongly advised to validate the spelling errors, if any, as the certification will reflect any error in this regard.

In case, at any stage candidate wants to update the personal details like registered email id, mobile number or communication address, candidates are requested to write us at

2.       Who can attend?

a.       Minimum age of 20 for joining the course.

b.      Students, working people or those how what to change the career to software development can Join the course.

c.       Basic Idea for programming will be the added advantage


3.       Admission

Admission to a programme is subject to aspirant fulfilling policies & procedures laid down by the SaNDS LabTM  academic division for the programme for which the participant is seeking admission. Admission of a participant in apProgramme shall be subject to an aspirant’s:

a) Meeting the eligibility criteria for the programme as laid out by the institute in terms of academic qualifications, experience as judged by the institute’s selection committee.

b) The actual realization of requisite fees as required, like application fees, registration fees, etc., as applicable. SaNDS LabTM  academic division reserves the right to cancel enrolment or even certification of any candidate at any stage of the programme in case any irregularity in participant’s eligibility or in other credentials is detected, and such action shall be in a sole discretion of SaNDS LabTM  academic division.


4.       Attendance

Most programmes have minimum attendance criteria. If your programme has minimum attendance criteria, attending classes for the programme on a regular basis is a mandatory requirement for successful completion of the programme and certification. The percentage criteria are different for each programme offered by the institute, and in case a candidate fails to fulfil the attendance criteria, the institute may not award the completion certificate to the participant.

In case of any discrepancy in attendance recording, verifications shall be carried out by SaNDS LabTM  and the institute using the attendance records available. The decision of SaNDS LabTM  and the institute in this regard shall be final & binding.

If your programme has online classes,. there is a standard sequence of logging into the system. A participant joining late or leaving early may not be granted attendance, since the system records login, logout, and the disconnection/reconnection time stamp.

You are required to login into the online classes using the email id you gave us when you registered for the programme. If improper login with incorrect email id/name is recorded in the system, a candidate is likely to be marked absent in this case


5.       Fee Payment & Due Dates

Fees are required to be paid as per the prescribed installment plan, and no extensions shall be granted for paying the due installment under any circumstance.

Candidate must refer “FEE STRUCTURE” for installment dates and amounts.

The fee is only accepted in the form of Online Card Payment/UPI/Bank Transfer.

SaNDS LabTM  system shall automatically disable the participants if the due payment is not received within seven (7) days of the due date (participants in debit balance continues more than seven (7) days).

This status in the system is called “On-break‟ due to non-payment.

The participant’s login credentials and ILS invites would be enabled within three (3) working days of participant’s payment credited in the bank.

Fee once paid, it is neither refundable nor transferable towards any other participant/ Programme/ post programme commences.

Beyond 10 days from the due date, a “forced withdrawal” student will be allowed to rejoin the programme with the rejoining fee of Rs.2,000/- (Rupees two thousand only). Any student who goes on “Forced withdrawal” more than once in a programme will not be allowed to rejoin the programme.


6.       Break from the programme and rejoining

A student may make a request for break from a programme giving details of reasons for such a request. In case SaNDS LabTM  academic division is satisfied with the reasons for seeking break from a programme, (in exceptional cases) it may be allowed, subject to student not in any form of default- payment or academic. However permission to seek break does not automatically provide a right to rejoin any subsequent batch of the same programme & specific approval process has to be followed as below:

• Payment of differential fees as applicable to the repeat programme as compared to discontinued/existing batch.

• Payment of rejoining fee which is currently Rs 10,000 plus applicable taxes.

• Participant must complete a program within a time frame not longer than next cohort, in case of break & rejoins.

• Request for break with adequate details may be submitted to


7.       Cancellation/Refund Policy

All notification of cancellations/withdrawals from the programme must be received in writing by SaNDS Lab 15 days or more before the programme start date.

• Where the request for refund of academic fees has been received prior to the cut-off date, the refund shall be made for an amount equal to the academic fees after deducting a refund processing penalty

• To know more about the panelty amount you are requested to write to

• The amount of taxes collected from the participant shall not be refunded.

• Where the refund is being made on account of the programme is canceled, the refund shall be made for the entire amount, including taxes collected from the participant. No penalty shall be imposed in this case.

• Where the request for refund has been received subsequent to the rescheduling of the start date of the programme that results in the programme commencement being delayed by more than one month from the original commencement date, the refund shall be made for an amount equal to the academic fees and the amount of taxes collected from the participant. No request for refund on account of rescheduling of the start date of the programme shall be considered if the programme commencement is delayed by less than one month.

• No refund shall be made after the commencement of the programme


8.       Taxes

Any taxes or duties (“Taxes”) imposed/assessed by the Central Government, local authority or any other Government Department or statuary authority by virtue of any enactment or amendment to the existing statutes or otherwise in respect of the programme being conducted by SaNDS Lab TM shall be payable by the participants as and when the same gets applicable. The participants shall be liable to pay the same immediately, which may be before, after, or during the term of the programme. SaNDS LabTM  reserves the right to take any action it deems fit if the participant does not pay such taxes to SaNDS LabTM

9.       Certificate

Certificates are being issued by institute only subject to completion of programme successfully as per individual institute’s policy & process. Generally, it’s done on

• Successfully completion of examination & assessment if any

• Maintaining attendance criteria of the programme

• No due certificates from SaNDS LabTM   Academics department.

Note:- SaNDS LabTM  will issue the digital certificate after successfully completing the course it may take 15 to 20 working days. If you need hard copy of the certificate the cost will be 300/- Rupees and it will send to your registered address by courier. If any quires please write to

Note:- SaNDS LabTM  is not providing any job guarantee after the training program. To learn more, please contact us at or call 9895765626.

Week 1 (Introduction of Python)
- o Basic Syntax
- o Handling Variables
- o Getting the Data Type
- o Specify a Variable Type
- o Slicing Strings
- o Modify Strings
- o String Concatenation
- o Escape Character
- o String Methods
- o Booleans
- o Operators
Week 2 (File, List, Tuples)
- o File Handling
- o Standard Deviation Basic concept
- o Access List Items
- o Change List Items
- o Add List Items
- o Remove List Items
- o Loop Lists
- o List Comprehension
- o Sort Lists
- o Copy Lists
- o Join Lists/dd>
- o List Methods
- o Access Tuples
- o Update Tuples
- o Unpack Tuples
- o Loop Tuples
- o Join Tuples
- o uple Methods
Week 3 (Set, Dictionaries, Loop, Functions, Lambda, Arrays)
- o Access Set Items
- o Add Set Items
- o Remove Set Items
- o Loop Sets
- o Join Sets
- o Set Methods
- o Access Items
- o Change Items
- o Add Items
- o Remove Items
- o Loop Dictionaries
- o Copy Dictionaries
- o Nested Dictionaries
- o Dictionary Methods
- o For
- o While
- o Functions
- o Lambda
- o Arrays
week 4 (Introduction to Data Science, Advanced Functions, Data Manipulation and Analysis with Pandas)
- o Popular Data Science Packages in Python
- o Packages
- o Getting Started with NumPy Arrays
- o Getting Started with 2D NumPy Arrays
- o Looping Over NumPy Arrays
- o Getting Started with Pandas Creating DataFrames
- o Getting Started with Pandas Slicing and Filtering DataFrames
- o NumPy and Pandas Statistical Tools
- o Adopting a Data Scientist's Mindset: Packages
- o Functions Review
- o Global Scope vs Local Scope
- o Nested Functions
- o Default and Flexible Arguments
- o Handling Errors and Exceptions
- o Writing Lambda Functions
- o Importing and Exporting Data
- o Introduction to Pandas Objects Part 1: Series
- o Introduction to Pandas Objects Part 2: DataFrames
- o Introduction to Pandas Objects Part 3: Common Functionality
- o Indexing and Selecting
- o Editing DataFrames Part 1: Setting Columns
- o Editing DataFrames Part 2: Transforming Columns
- o Editing DataFrames Part 3: Setting Data with loc[]
- o Combining DataFrames
- o Reshaping DataFrames
- o Grouping and Aggregating Data
Week 5 (Random Variables and Statistical Inferences, Introduction to Linear Algebra, Statistical Distributions and Hypothesis Testing)
- o Probability and Statistics
- o Probability vs. Statistics in Python
- o Sampling Using Python
- o Random Variables and Probability Distribution Functions
- o Random Variables and Probability Distribution Functions in Python
- o Probability Mass and Probability Density Functions
- o Matrices and Vectors
- o Matrix Addition and Subtraction
- o Dot Product and Cross Product
- o Matrix Multiplication and Division
- o Matrix Transposition
- o Uniform Distribution
- o Bernoulli and Binomial Distributions
- o Normal Distribution
- o Exponential, Poisson, and T Distributions
- o Confidence Intervals
- o Hypothesis Testing
Week 6 (Data Engineering, Data Storage, Data Visualization)
- o Data Cleaning
- o Data Normalization
- o Bias and Variance
- o Detecting Outliers
- o Handling Outliers
- o Imputation Techniques for Missing Data
- o Handling Unbalanced Data
- o Binning
- o Transforming Data
- o CRUD
- o Data Retrieval
- o Data Visualization with Matplotlib
- o Matplotlib, Seaborn
Week 7 (Data Visualization in Python With Plots, Classification and Decision Trees, Time Series Forecasting)
- o Simple Line Plots
- o Bar Plots
- o Scatter Plots
- o Histograms
- o Line of Best Fit
- o Pair Plots
- o AI, ML, DS and DA
- o Logistic Regression
- o Regression using Moon Data
- o Time Series Data
- o Stationary and Non-stationary Series
- o ARIMA for Forecasting
- o Time Series Forecasting
Week 8(Exploratory Data Analysis, Text Analysis, Data Collections Different Method and Approaches)
- o Linear and Non-linear Relationships Between Variables
- o Exploratory Data Analysis
- o Outlier Detection
- o Sentiment Analysis
- o Read Data from Text
- o Read Data from Database
- o Read Data from Images
- o Word Cloud Approach
- o Object Identification from Images
- o Objects Identification from Video
- o Data collection from Audio

Ajit Kumar K.V

Mr. Ajit Kumar is our Master Trainer and the CEO of the Company having more than 22 years of Experience in Software Development and IT Training, basically he is an Aeronautical Engineer and he changed his career to IT, from last 2 decades, he has the solid experience in Hardware Integrations and Software Development with different technologies.

He is the Award Winner from STPI (Software Technology Parks of India) in 2016 on “Make in India Pavilion”.

He has completed Applied Data Science from IIT

Card image cap

"The content of the certificate may vary depends upon the course completed."