Python For Data Science Certificate Course
Self Paced
 Fee:  ₹5,999 ₹699
 Dr. S. Veenadhari | Dean (Computer Science Engineering)
                                                                                                                            Dr. S. Veenadhari | Dean (Computer Science Engineering) Rabindranath Tagore University, Raisen, Madhya Pradesh
Integrate Python in your data science learning as it is one of today’s fastest-growing and versatile programming languages with relevance in data science, software development, machine learning, and AI.
Objectives
At the end of this course
Acquire an in-depth knowledge of the most dominant technologies in data science
Data manipulation and data analysis tools
Python statistics
Data visualization using python essentials.
What Will You Learn
Upon completing this course, you will independently be able to set up a python coding environment. Not only that, you will also be able to debug python code and python running programs along with the ability to visualize and analyze it. Manipulating data and performing statistical operations as well as design, code and test python functions that meet the needs of the data science industry is another skill set you will acquire.
Skills you will gain
Prepare for your career path
Python developers are computer programmers who specialize in writing server-side web application logic to develop, debug, and implement application projects.
Key Skills to Learn
Data Science, Data Visualization, Programming - Python, R, SQL etc, Mathematics & Statistics & Database Knowledge
As a data scientist, one would have to collect, analyze and interpret intensive data with the use of analytics technologies, including machine learning and predictive modeling. The role of a data scientist is usually derivative of various conventionals roles such that of a mathematician, scientist, statistician and computer professional.
Key Skills to Learn
Data Science, Data Visualization, Programming - Python, R, SQL etc, Mathematics & Statistics, Machine Learning, Database Knowledge
The ones who convert business requirements into technology requirements while defining data standards and principles are the senior visionaries in the data science field- the data architects. Not only that but they are also incharge of designing an organisations management framework which is the process of planning, specifying, enabling, creating, acquiring, maintaining, using, archiving, retrieving, controlling, and purging data.
Key Skills to Learn
System Development Life Cycle, Data Science, Data Visualization, Predictive analytics and Unstructured data, Programming Python, R, SQL etc, SQL development and database administration, Big Data, Mathematics & Statistics, Machine Learning
Jobs in India
 
                                                                    1.6 Lakh+
Average Salary
 
                                                                    6 Lakhs
Job Growth
 
                                                        33%
Learn from the industry experts and stay ahead of the curve
 
                                                                                             
                                                                                             
                                                                                             
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                                                                            Curriculum
- 
                                                            What is Data Science- 
                                                                                 Introduction to Data Science
                                                                                    5:19 Introduction to Data Science
                                                                                    5:19
- 
                                                                                 Real Life examples with applications
                                                                                    6:51 Real Life examples with applications
                                                                                    6:51
- 
                                                                                 Data Scientist Job roles and responsibilities
                                                                                    3:20 Data Scientist Job roles and responsibilities
                                                                                    3:20
- 
                                                                                 The most promising Job of the 21st Century
                                                                                    9:24 The most promising Job of the 21st Century
                                                                                    9:24
- 
                                                                                 Machine Learning vs. Data Science vs. AI
                                                                                    19:06 Machine Learning vs. Data Science vs. AI
                                                                                    19:06
 
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- 
                                                            Introduction to Python- 
                                                                                 Python Introduction
                                                                                    05:02 Python Introduction
                                                                                    05:02
- 
                                                                                 Installation of Anaconda Navigator
                                                                                    07:27 Installation of Anaconda Navigator
                                                                                    07:27
- 
                                                                                 Jupyter Notebook Interface
                                                                                    09:26 Jupyter Notebook Interface
                                                                                    09:26
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                                                                                 How to open, save and rename a file
                                                                                    04:54 How to open, save and rename a file
                                                                                    04:54
- 
                                                                                 Variables and Data Types
                                                                                    09:53 Variables and Data Types
                                                                                    09:53
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                                                                                 Python Strings
                                                                                    18:45 Python Strings
                                                                                    18:45
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                                                                                 Loops (Conditional)
                                                                                    16:25 Loops (Conditional)
                                                                                    16:25
- 
                                                                                 Loops (iterative while)
                                                                                    11:57 Loops (iterative while)
                                                                                    11:57
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                                                                                 Loops (iterative For)
                                                                                    12:28 Loops (iterative For)
                                                                                    12:28
- 
                                                                                 Python Functions (Built in,Lambda,User defined functions)
                                                                                    20:13 Python Functions (Built in,Lambda,User defined functions)
                                                                                    20:13
- 
                                                                                 Lists
                                                                                    10:30 Lists
                                                                                    10:30
- 
                                                                                 Tuples
                                                                                    11:52 Tuples
                                                                                    11:52
- 
                                                                                 Sets
                                                                                    15:00 Sets
                                                                                    15:00
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                                                                                 Dictionaries
                                                                                    20:00 Dictionaries
                                                                                    20:00
 
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                                                            Data Manipulation and Data Analysis Tools- 
                                                                                 NumPy Arrays in Python
                                                                                    19:08 NumPy Arrays in Python
                                                                                    19:08
- 
                                                                                 Three Dimensional Arrays Indexing and slicing
                                                                                    15:24 Three Dimensional Arrays Indexing and slicing
                                                                                    15:24
- 
                                                                                 Matrices
                                                                                    15:04 Matrices
                                                                                    15:04
- 
                                                                                 Pandas in Python
                                                                                    10:08 Pandas in Python
                                                                                    10:08
- 
                                                                                 Importing CSV, Excel Files
                                                                                    07:45 Importing CSV, Excel Files
                                                                                    07:45
- 
                                                                                 Exporting CSV file
                                                                                    05:01 Exporting CSV file
                                                                                    05:01
 
- 
                                                                                
- 
                                                            Python Analysis- 
                                                                                 Basic descriptive statistics with Numpy and  Applying statistical functions on matrices
                                                                                    10:27 Basic descriptive statistics with Numpy and  Applying statistical functions on matrices
                                                                                    10:27
- 
                                                                                 Linear Algebra with NumPy
                                                                                    25:18 Linear Algebra with NumPy
                                                                                    25:18
- 
                                                                                 NumPy Random Numbers
                                                                                    19:53 NumPy Random Numbers
                                                                                    19:53
- 
                                                                                 Probability distributions using NumPy
                                                                                    21:35 Probability distributions using NumPy
                                                                                    21:35
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                                                                                 Normality test with SciPy
                                                                                    15:49 Normality test with SciPy
                                                                                    15:49
 
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- 
                                                            Data Visualization in Python- 
                                                                                 The Matplotlib package
                                                                                    15:01 The Matplotlib package
                                                                                    15:01
- 
                                                                                 Basic Matplotlib plots
                                                                                    18:57 Basic Matplotlib plots
                                                                                    18:57
- 
                                                                                 Logarithmic plots
                                                                                    13:41 Logarithmic plots
                                                                                    13:41
- 
                                                                                 Scatter plots
                                                                                    16:52 Scatter plots
                                                                                    16:52
- 
                                                                                 Three Dimensional plots
                                                                                    25:51 Three Dimensional plots
                                                                                    25:51
- 
                                                                                 Lag plots
                                                                                    15:33 Lag plots
                                                                                    15:33
- 
                                                                                 Autocorrelation Plots
                                                                                    9:50 Autocorrelation Plots
                                                                                    9:50
- 
                                                                                 Plot.ly
                                                                                    16:56 Plot.ly
                                                                                    16:56
 
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                                                            Applications in Industry - BFSI- 
                                                                                 In consultation with Industry experts
                                                                                    1:00:00 In consultation with Industry experts
                                                                                    1:00:00
 
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Instructor
 
                                                                                                                    Dr. S. Veenadhari
Dean (Computer Science Engineering) Rabindranath Tagore University, Raisen, Madhya PradeshPresently she is working as a Dean in Computer Science Engineering department at Rabindranath Tagore University, Bhopal. She is having over 20 years of academic and research experience. Under her guidance more than 10 students completed their doctoral programmes in the field of Machine Learning and Data Science.
 
                                                                                                                    Dr. Avik Sarkar
Faculty, Indian School of Business, Areas: Analytics, Data, Technology & Public PolicyDr. Avik Sarkar is Faculty at Indian School of Business working in the areas of Data, Emerging Technology and Public Policy. At ISB, Dr Sarkar is heading the development of India Data Portal (www.indiadataportal.com), one stop portal for analysis and visualization of government data and working on the societal & policy aspects related to use of emerging technologies like artificial intelligence trustworthiness, ethics, data privacy, e-commerce policy, etc. Dr. Sarkar was the former Head of Data Analytics Cell and Officer on Special Duty (OSD) at NITI Aayog (National Institution for Transforming India Aayog) premier policy think-tank of Government of India
Still have queries? Talk to our counselors who are available to guide you.
Shareable Certificate
 
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 Level
                                                        Level                                                     Credentials
                                                        Credentials                                                      ₹5,999 ₹699
Get job assistance and jumpstart your career as Data Scientist
 
                                                             
                                                             
                                                             
                                                             
                                                            Trusted By Learners

Swati Sonal
Data Science course helped me in skills upgradation during my graduation which also resulted in good job opportunity at Wipro.

Himanshu Chauhan
I got the best learning experience in Python for Data Science Course through Subject Matter Experts from Industry. Live Classes and capstone projects helped me getting best hands on learning experience.
FAQs
- 
                                                        What are the best Data Science & Python Programming certifications I can go for?If you're looking to evaluate your options when it comes to Data Science and Python certifications, AISECT provides you with a plethora of options including- Python for Data Science Advance Certificate Course Data Science using Python Certificate Course Python for Data Science Certificate Course Data Science & Machine Learning Foundation Course Data Visualization in Python Advance Certificate Course Python for Data Science Bootcamp Certificate Course Python for Data Science Advance Certificate Course 
- 
                                                        What are the Jobs options you will have once you complete this certification course online?Your scope in the field of python is quite vast once you finish a certificate course. You can apply for jobs on websites like Indeed.com which has over 40,000 job listings that require Python programming experience or skills. There are job titles such as Python Developer, Python Software Engineer and Full Stack Developer that you can apply for. The salaries for Python-specific jobs are 43% higher than $100K annually, while some senior-level Python programming engineers earn over $200K per annum. Having the adequate skills for python can overall lead to a secure career path. 
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                                                        What are the present career paths in Data Science?Following an online certification in data science, python experts can apply for jobs for titles such as Data Scientist, Data Analyst, Data Engineer & Business Intelligence Developer. The job description for these positions may include using Python to create, edit or manage software along with testing and debugging code or building websites. After getting acquainted with Python, it also becomes easier to work in finance, education, project management, computation, or financial services. 
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                                                        How soon after signing up would I get access to the learning content?Following enrollment, you will be given immediate access to the LMS, which will be available to you for the next year. You'll get full access to all past class recordings, PPTs, PDFs, and assignments. In addition, you will have immediate access to our 24-hour support team. You may immediately begin learning. 
- 
                                                        Will I Get Placement Assistance After Completing My Python Online Course?More than 70% of AISECT learners have reported changes in job profile (promotion), work location (onsite), lateral transfers & new job offers. AISECT Learn's Python Course is well recognized in the IT industry as it is a testament to the intensive and practical learning you have gone through and the real-life projects you have delivered. 
- 
                                                        Who are trainers in these certificate programs in Data Science and Machine Learning?The instructors for these programs are industry experts who are highly efficient and well-informed in this field. Video lessons by top faculty from RTNU, Bhopal will also be provided to you. 
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                                                        What certificate will I be given on course completion?You will receive an industry-recognized certification post completion of the paid programs. 
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                                                        Do you offer financing options?We value the candidates who wish to learn but do not have the financial bandwidth to make an upfront payment of the fees. Hence, AISECT Learn in tie-up with financing partners offers an easy EMI option to the candidates. 
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