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Applied Data Science with Python in collaboration with IBM

The Data Science with Python certification course provides a complete overview of Python's Data Analytics tools and techniques. Learning Python is a crucial skill for many Data Science roles. Acquiring knowledge in Python will be the key to unlock your career as a Data Scientist.

Program Overview

The Python Data Science course teaches you to master the concepts of Python programming. Through this Data Science with Python certification training, you will learn Data Analysis, Machine Learning, Data Visualization, Web Scraping, & NLP. Upon course completion, you will master the essential tools of Data Science with Python.

Key Highlights

  • 68 hours of blended learning68 hours of blended learning
  • 4 industry-based projects4 industry-based projects
  • Interactive learningInteractive learning
  • Dedicated mentoring session from faculty of industry expertsDedicated mentoring session from faculty of industry experts

Applied Data Science with Python in collaboration with IBM

  1. 80000
    10000+ learner
Features
  • 100+ hours of learning
  • Practice Test Included
  • Certificate of completion
  • Skill level

Languages and Tools covered

Applied Data Science with Python in collaboration with IBM

Get eligible for 3 world-class certifications thus adding that extra edge to your resume.

  • Alumni Status
  • Learning paths and certification from IBM
  • Course completion certificate from DataTrained Education
  • Project completion certificate from DataTrained Education

What’s the focus of this course?

Choose from specializations, receive industry mentorship, dedicated
career support, learn 14+ programming tools & languages & much more

Unique Specializations- data science programs near me

Uniquely Designed Curriculum

Starting from foundations of programming to building projects based real-time solutions. Get a globally recognized certification In Applied Data Science In Collaboration With IBM.

Dedicated Career Assistance- data science program institute

Dedicated Career Assistance

Receive 1:1 career counselling session & mock interviews with hiring managers. Exhilarate your career with our 400+ hiring partners.

Student Support -  data science online training

Student Support

Student support available 09 AM to 09 PM IST via email or use the call Back option on the Platform to get a response within 2 working hours.

Instructors

Learn from India’s leading Software Engineering faculty and Industry leaders

Dr. Deepika Sharma - Training Head, DataTrained
Dr. Deepika Sharma
Training Head, DataTrained

Research Scientist with a PhD in computer science and 14 years of hands-on experience.

Polong Lin - Business Analyst, IBM
Polong Lin
Business Analyst, IBM

Polong Lin is a Data Scientist at IBM in Canada. Under the Emerging Technologies division, Polong is responsible for educating the next generation of data scientists through BDU.

Jay Rajasekharan- Data Scientist, IBM
Jay Rajasekharan
Data Scientist, IBM

Currently, he is driving several productivity programs - using data analytics to drive insights from business operations and implementing optimizations such as streamlining workflows, improving service levels, and ultimately reducing cost.

Mahdi Noorian- Data Scientist, IBM
Mahdi Noorian
Data Scientist, IBM

Mahdi Noorian is a Postdoctoral Fellow at the Laboratory for Systems, Software and Semantics (LS3) of the Ryerson University. He holds a Ph.D degree in Computer Science from University of New Brunswick.

SYLLABUS

Best-in-class content by leading faculty and industry leaders in the form of cases, videos and projects, live sessions and assignments.

best data science courses online

Syllabus

This course offers a beginner-friendly launch to Python for Data Science. Practice through lab workouts, and you will be prepared to design your very first Python scripts on one's own!

Course Content
Module 1 - Python Basics
  • Your first program
  • Types
  • Expressions and Variables
  • String Operations
Module 3 - Python Programming Fundamentals
  • Conditions and Branching
  • Loops
  • Functions
  • Objects and Classes
Module 2 - Python Data Structures
  • Lists and Tuples
  • Sets
  • Dictionaries
Module 4 - Working with Data in Python
  • Reading files with open
  • Writing files with open
  • Loading data with Pandas
  • Working with and Saving data with Pandas

With this program, you are going to learn the right way to evaluate data in Python using multidimensional arrays in NumPy, control DataFrames in pandas, make use of the SciPy library of mathematical actions, as well as conduct machine learning using scikit learn! You are going to learn the right way to do data analytics in Python making use of these popular Python libraries and you'll do it using hands-on labs using genuine Python tools as Jupyter notebook in JupyterLab.

Course Content
Module 1 - Importing Datasets
  • Understanding the Dataset
  • Python package for data science
  • Importing and Exporting Data in Python
  • Basic Insights from Datasets
Module 3 – Pandas
  • Python Pandas - Introduction
  • Introduction to Data Structures
  • Python Pandas - Series
  • Python Pandas - DataFrame
  • Python Pandas – Indexing & Re-indexing Columns
  • Python Pandas - Sorting
  • Python Pandas - Aggregations
  • Python Pandas - Missing Data
  • Python Pandas - GroupBy
  • Python Pandas - Merging/Joining
  • Python Pandas - Concatenation
  • Python Pandas - Visualization
  • Python Pandas - Correlation
  • Python Pandas – Describe Function
Module 2 – NumPy
  • NumPy - Introduction
  • NumPy - Ndarray Object
  • NumPy - Data Types
  • NumPy – Shaping & Reshaping
  • NumPy – Random Numbers
  • NumPy - Indexing & Slicing
  • NumPy – Handling Missing Data
  • NumPy - Arithmetic Operations
  • NumPy - Statistical Functions (Min-Max Function) Sort, Search & Counting Functions
Module 4 – Descriptive & Inferential Statistics
  • Mean, Median, Mode
  • Range, Percentile, Variance,
  • standard deviation,
  • Probability distribution
  • Binomial distribution
  • Normal distribution
  • Poisson distribution
  • Normal curve
  • Bell curve
  • Skewness
  • zscore
  • Hypothesis Testing
  • p-value
  • Statistical Parametric Test
  • Covariance
  • Statistical correlations,

This course offers a beginner-friendly launch to Python for Data Science. Practice through lab workouts, and you will be prepared to design your very first Python scripts on one's own!

Course Content
Module 1 - Python Basics
  • Your first program
  • Types
  • Expressions and Variables
  • String Operations
Module 3 - Python Programming Fundamentals
  • Conditions and Branching
  • Loops
  • Functions
  • Objects and Classes
Module 2 - Python Data Structures
  • Lists and Tuples
  • Sets
  • Dictionaries
Module 4 - Working with Data in Python
  • Reading files with open
  • Writing files with open
  • Loading data with Pandas
  • Working with and Saving data with Pandas

This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!

Course Content
Module 1 -Supervised vs Unsupervised Learning
  • Machine Learning vs Statistical Modelling
  • Supervised vs Unsupervised Learning
  • Supervised Learning Classification
  • Unsupervised Learning
Module 3 - Supervised Learning II
  • Regression Algorithms
  • Model Evaluation
  • Model Evaluation: Overfitting & Underfitting
  • Understanding Different Evaluation Models
Module 5 - Dimensionality Reduction & Collaborative Filtering
  • Dimensionality Reduction: Feature Extraction & Selection
  • Collaborative Filtering & Its Challenges
Module 2 -Supervised Learning I
  • K-Nearest Neighbors
  • Decision Trees
  • Random Forests
  • Reliability of Random Forests
  • Advantages & Disadvantages of Decision Trees
Module 4 - Unsupervised Learning
  • K-Means Clustering plus Advantages & Disadvantages
  • Hierarchical Clustering plus Advantages & Disadvantages
  • Measuring the Distances Between Clusters - Single Linkage
  • Clustering
  • Measuring the Distances Between Clusters - Algorithms for
  • Hierarchy Clustering
  • Density-Based Clustering

Comprehensive Curriculum

The curriculum has been designed by faculty from IITs and Expert Industry Professionals.

100+ Hours of Content--- data science program institute
100+

Hours of Content

80+ Live Sessions--  data science online training
80+

Live Sessions

15 Tools and Software- best tools for data science
15

Tools and Software

Download Curriculum cum Brochure

Career Impact

DataTrained in collaboration with IBM presents the best online Applied Data Science With Python in India. Over 500 Careers Transformed.

DataTrained has helped me with the vital knowledge and skills that are needed for a data scientist role. The trainer starts with an example to make us comprehend the concept and then help us build the algorithms with the real industry datasets.

Aruni Khare-- Data Scientist, RBS
Aruni Khare
Data Scientist, RBS

I saw an ad from DataTrained on facebook and I contacted them straight away and inquired about their Data Science online course. Their counselor took me through the complete journey of what they offer and what is data science all about. After continuous conversation for a few weeks, I was pretty sure about the course and now I knew where I need to invest my money and hard work.

Rakshit Jain- Data Scientist, Optum
Rakshit Jain
Data Scientist, Optum

The program is a well-balanced mix of pre-recorded classes, live sessions on weekends and printed reading materials they sent to my address. My mentor was Amit Kaushik and he helped me in getting that confidence and completing my assignments on time.I have almost completed the course and have been able to crack Glenmark interview.Thank you so much DataTrained.

Rupam Kumar Chaurasia-- Head Sales, Glenmark
Rupam Kumar Chaurasia
Head Sales, Glenmark

Once I Joined DataTrained my learning curve started to grow steeply and as per the mentors I followed the new approach to get Data Science job.If I am successfully placed with one of the biggest data science firm complete credit lies with DataTrained and their competent Faculty.

Vanshika Rathi-- Data Analyst, Ola
Vanshika Rathi
Data Analyst, Ola

I did my research before deciding which course I should register myself for and of all the courses that I have found, the one offered by DataTrained was completely dedicated to analytics, after enrolling for Postgraduate Program for Data Science, I realized DataTrained Data Science course was ideal for me.

Surbhi Jain-- Sr. Data Specialist, Bank of America
Surbhi Jain
Sr. Data Specialist, Bank of America

All faculty members in DataTrained are well known and they are available round the clock to discuss any course related query.After completing my course I was so confident and cracked my first Interview with Amazon and I have completed a successful 1 year with them. Big thanks to DataTrained to help me in selecting a perfect job for me.

Saurabh Chauhan--Data Analyst, KPMG India
Saurabh Chauhan
Data Analyst, KPMG India

Admission Process

There are 3 simple steps in the Admission Process which is detailed below

Step 1: Fill in a Query Form

Fill up the Query Form and one of our counselors will call you & understand your eligibility.

Step 2: Get Shortlisted & Receive a Call

Our Admissions Committee will review your profile. Upon qualifying, an Email will be sent to you confirming your admission to the Program.

Step 3: Block your Seat & Begin the Prep Course

Block your seat with a payment of INR 10,000 to enroll in the program. Begin with your Prep course and start your Data Science with python journey!

Program Fee

₹ 80000 + 18% GST

No Cost EMI options are also available. *

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I’m interested in this program

What's Included in the Price

Industry recognized certificate from IBM

Access to 15 real life projects and a capstone project

IBM Watson labs and $1200 equivalent Cloud Credits

For Queries and Suggestions

Call DataTrained Now
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Frequently Ask Questions

Yes, you will get a certificate from DataTrained for the course completion as well as a project completion certificate from DataTrained.

There are two types of projects:

A. Practice projects: Your mentor will first do 2-3 projects for you and then you will do the next 3-4 projects wherein you will get help from your mentor and on tickets.

B. Evaluation projects: Once you’re done with the practice projects, you get access to the evaluation projects.

Data Science doesn’t need any previous technical or programming experience. We will teach you Math, Stats and programming at a very beginner level.

No, the program is designed in such a way that, you can continue with your job along with this program. It will be a mix of pre-recorded videos, live classes as well as printed study material. Every topic would be project-based and will be taught as per the live market scenario. The course module will be covered under the guidance of Industry Experts.

There are two training modes:

A. Self-paced: You will get access to DataTrained and IBM joint LMS wherein you will be assigned courses and projects. You will need to go through these courses and complete the projects at your own pace. Mentor support will be provided.

B. Blended: You will get access to DataTrained and IBM joint LMS wherein you will be assigned courses and projects. You will need to go through these courses and complete the projects at your own pace. In addition to these courses, live online classes are conducted on Saturdays and Sundays for you. Mentor support will be provided.

In case you miss a class, you need not to worry. All the live classes’ recordings will be available on your LMS. You can watch and practice the concepts at your own time.

We have partnered with analyticsjobs.in for the placement assistance for our learners who successfully completes our programs. Analytics Jobs is a leading media and job portal company specifically aimed for the jobs in Data Science, Analytics, Automation, RPA, Cloud, Block Chain and computer science.