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Data Science with Python Certification Training Course in Bangalore With Placement Assurance
Become an IABAC Certified Data scientist in 6 weeks, with 100% money back guaranteed if you are not happy with the training.
2000+ Ratings
3000+ Happy Learners
Data Science with Python Videos
Skills Covered in Data Science
Python full coding from scratch
Visualization with Python
Machine Learning with Python - 6 different algorithms
Robotic Automation
Multiple Linear regression
Logistic regression
Cluster Analysis
SQL queries(with Python)
Machine Learning Fundamentals
Data Manipulation with Pandas
Statistical Analysis with Python
Supervised and Unsupervised Learning
Building Predictive Models
Time Series Analysis
Model Evaluation and Optimization
Data Science Training Key Features
63 Hrs Practical Sessions
Assured Job Placement
Professional Resume building
Interview Preparation Session
Classroom & Online Training
Delivered by Industry Experts
18 Case studies on Machine Learning
Certification Guidance
1 Year Access to Recorded Sessions
Zero-Interest EMI Option
Designated Placement Advisor
Weekly Practice Assignments
Placement assistance will be provided
Cloud Computing course offered as complimentary
Our Alumni Working in
Data Science Course Reviews
Resham Rajpal
Data Science Expert
The training at Apponix made me more confident in Data analysis. I have completed Data Science training form here. Excellent classes that helped a lot.
Ajith Bahadhur
Data Science Analyst
My experience with Apponix was really great. The trainer provided a lot of practical training. He is an expert. Each topic was taught through proper practical classes.
Mahesh Mahi
Data Science Analyst
I took Data Science training from the institute. I am happy to make Apponix as my choice. Too good labs and sessions are handled here.
Lakshana Senthil
Data Engineer
Management is very good, flexible with timings. Teaching pattern is easy and understandable.
Bijal Patel
Data Analyst
Best institute for Data Science. Trainer has very good knowledge in Data Science.
Aarsh Mehta
Data Engineer
Sir is very helpful and takes every step to make the students understand topics.
Our Recent Placements
Classroom Training
Classroom Training
Fees & Training Options
Class room Training
- Interactive Classroom Training Sessions
- 60+ Hrs Practical Learning
- Guaranteed 8 Interview Arrangements
- Excellent Classroom Infrastructure
- Placement Assurance
- Delivered by Working Professionals
- Weekdays & Weekend batches
- Authorized IABAC Training Delivery
Online Training
- Interactive Live Training Sessions
- 60+ Hrs Practical Learning
- Delivered by Working Professionals
- 1 Year Access to Recorded Sessions
- Placement assistance will be provided
- Daily 2 Hrs or Weekend 10 Hrs
- Weekdays & Weekend batches
- Authorized IABAC Training Delivery
- Doubt Clearing Sessions
- Regular assignments will be given and assessments will be taken.
Data Science Training Syllabus
Prerequisites
No prerequisites for learning data science but if you have some previous knowldge on computer science & statistics it helps you a lot in understanding subjects fast.
Secondly, you need to have an analytical mind – that is all you would need to enroll for Statistics For Data Science Courses.
Data Science Course Syllabus
Overview of the course
Class 1: Introduction to Python Programming Language
- Introduction and Installation of Python software Python packages: Pandas, & Numpy
- Concepts of Data frame Filtering
- Loc and iloc for filtering Usage of Boolean in Filtering Appending
Class 2: Data handling in Python
- Handling of Missing values If else statement
- Extra trick of using if else statement Removal of Duplicates
- Frequency Distribution
- Merging – Inner, Outer, Left and Right Binding and Appending
- Descriptive Statistics o Inbuilt Numeric functions of R
Class 3: More data handling using Python
- Pivot Table of Excel in Python Grouping function
- Learning of SQL queries using Python Grouping numeric data
Class 4: Additional functions of Python
- Text functions
- Data cleaning with efficient text functions Inbuilt String functions of Python Reshape functions of Python
Class 5: Statistics
- Everything you want to know about statistics….Well sort of!! Mean, Median, Mode
- Standard Deviation, Variance, Normal Distribution Hypothesis testing
- T-test, Anova, Normality test
Class 6: Linear Regression
Class 7 : Linear Regression Practice Case Study
- Predictive Analytics – Linear Regression Concepts of Linear Regression
- Simple and Multiple Linear Regression Automatic Dummy Variablescreation technique Model Validation parameters
- Model Assumption testing
- Splitting of data for Validation and testing
- Business Case Study with real data to model in Python
Participants will be asked to develop a Linear Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.
Class 8: Logistic Regression
Class 9: Logistic Regression Practice Case Study
- Predictive Analytics – Logistic Regression Concepts of LogisticRegression
- Difference between Linear Regression and Logistic RegressionAutomatic Dummy Variables creation technique
- Model Validation parameters Model Assumption testing
- Splitting of data for Validation and testing
- Business Case Study with real data to model in Python
Participants will be asked to develop a Logistic Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.
Class 10: Time Series Forecasting
- Time series forecasting: ARIMA
- Difference between forecasting and prediction Concepts of time series data
- Concepts of ARIMA
- Descriptive analytics for ARIMA Development of model
- Best model selection Forecasting with the best model Residual analysis
- Business Case Study with real data to model in R software
- Participants will be asked to develop a model in presence of the instructor.
Class 11: Cluster Analysis
- Unsupervised Machine Learning with Python Cluster Analysis: Concepts
- Cluster analysis with Python – K Means, Hierarchical etc.
Class 12: Decision Tree and Random Forest
- Concepts of Decision Tree Decision Tree with Python Concepts ofRandom Forest Random Forest with Python
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Our Top Instructors
Mr Shubhojit
Work Experience:
Shubhojit brings over 14 years of experience in Analytics, having worked with top CMMI Level 5 companies such as The Nielsen Company and TCS, where he currently serves as a Senior Analytics Consultant.
He has domain expertise across Retail, BFSI, Energy, and Utilities, and specializes in Predictive Analytics, Machine Learning, and Simulation using tools like SAS, R, Python, and GMP.
Proficient in advanced algorithms including ANN, RNN, CNN, XGBoost, Naïve Bayes, and SVM. He has built classification, regression, and churn models using Python and R.
Experienced in NLP for sentiment analysis, topic modeling, and text analytics. He has also applied recommendation systems such as Collaborative Filtering and Market Basket Analysis.
Shubhojit has utilized tools like Power BI, Spotfire, and REST APIs for building insightful dashboards and data integration, and used Google Analytics and HotJar for web and customer behavior analytics.
Trained 250+ students and conducted corporate sessions for Genpact, HSBC, ITC, and Wipro; also invited to IIT Kharagpur for workshops.
He had also been invited to IIT Kharagpur several times, to conduct analytics workshops for their B-Tech students. He has founded Analytics Educator – a premium institute for pertaining analytics training to professionals.
Founder of Analytics Educator and associated with institutions like Apponix, IVY Pro School, and EduPristine for professional analytics training.
Santosh
Education:
Graduate of Oxford College, where I developed a strong foundation in data science and analytics.
Professional Experience:
With over 10 years of experience in the industry, I am currently a Senior Data Science Specialist at Microsoft, specializing in advanced data analytics solutions for leading MNCs.
Technical Skills & Key Technologies:
- Predictive Modeling: Building models to forecast outcomes using historical data.
- Natural Language Processing (NLP): Analyzing and interpreting text data for insights.
- Machine Learning with Python: Skilled in applying multiple ML algorithms to solve real-world problems.
- Data Visualization: Creating impactful visuals using Python for better data storytelling.
- Robotic Process Automation (RPA): Streamlining tasks and boosting efficiency through automation.
Student Success & Career Support:
- Trained over 1000 students at Apponix Academy with an average rating of 4.9. I provide:
- Career Mentorship: Resume building, mock interviews, and personalized job readiness coaching.
- Placement Support: Assisting students in securing roles at top organizations through industry-focused guidance.
Subojith
Education:
Graduate from CMR University, where I built a strong foundation in data science principles and practices.Professional Experience:
With 15+ years of experience in the data science domain, I currently serve as a Senior Data Science Manager at Capgemini, bringing deep insights and knowledge from various MNCs.Technical Skills:
- Logistic Regression: Skilled in statistical modeling for binary outcomes and predictive analysis.
- SQL Queries with Python: Proficient in data manipulation and analysis using integrated SQL and Python workflows.
- Time Series Analysis: Experienced in identifying trends and patterns in temporal data.
- Cloud Computing (AWS, Azure, GCP): Leveraging cloud platforms for scalable data storage and analytics.
Student Success & Career Support:
- Trained over 1500 students at Apponix Academy with an average rating of 4.9, offering strong career guidance through:
- Resume Building: Crafting job-ready, data science-focused resumes.
- Interview Prep: Conducting mock sessions and sharing strategic tips.
- Placement Support: Assisting students in landing roles across top companies.
Keerthan
Education:
Graduated from Reva University, where I laid the foundation for my expertise in data science.
Professional Experience:
With 9+ years of experience in the industry, I currently serve as a Senior Data Science Specialist at Wipro, bringing valuable insights from my work with various MNCs.
Technical Skills:
- Machine Learning with Python: Proficient in applying 6 different algorithms to solve real-world problems.
- Robotic Automation: Expertise in automating processes to enhance efficiency.
- Multiple Linear Regression: Skilled in statistical modeling to understand relationships between variables.
- Data Visualization: Utilizing tools like Tableau and Matplotlib to present insights effectively.
- Big Data Technologies: Experience with frameworks like Hadoop and Spark for large-scale data processing.
Student Success & Career Support:
- I have trained over 900 students at Apponix Academy, achieving an average rating of 4.8. My commitment to student success includes:
- Resume Building: Helping students craft impactful resumes tailored for data science roles.
- Interview Preparation: Providing practical guidance and mock interviews to enhance confidence and skills.
- Job Placement Assistance: Supporting students in navigating the job market to secure fulfilling positions.
Arpitha
Education:
Alumnus of St. Joseph’s College, where I honed my analytical skills and passion for data science.
Professional Experience:
With 12+ years of experience, I currently serve as a Senior Data Science Specialist at Amazon, where I apply my expertise to solve complex data challenges in a fast-paced environment.Technical Skills & Expertise:
- Data Engineering & Wrangling: Skilled in ETL processes, cleaning, and preparing data for analysis.
- Experimental Design & A/B Testing: Designing experiments to support data-driven decisions.
- Model Deployment & Time Series Analysis: Deploying models and analyzing sequential data trends.
- Computer Vision & Web Scraping: Extracting insights from images, videos, and online data sources.
- Big Data & Visualization: Proficient with Hadoop, Spark, and creating impactful data visualizations.
Student Success & Career Support:
- Trained over 1200 students at Apponix Academy with an average rating of 4.8. I offer end-to-end support through:
- Resume Building: Creating impactful, job-ready resumes.
- Interview Prep & Placement: Mock interviews and personalized guidance to secure data science roles.
Overview of Data Science Training Course
This course follows a curriculum that covers all the major aspects of data science such as machine learning,data integration, data architecture, data visualization, predictive analytics, etc.
Benefits of learning Data Science
Data science-related courses from Apponix will let you make the most out of the demand for skilled professionals in this sector so that you can land a high-paying job at your dream company.
With our data science certificate online or offline course, you will surely be able to have a competitive edge over other applicants interested to have a lucrative career in the field of data science.
Data Science related jobs
- Data Analyst
- Data Scientist
- Data Engineer
- Data Architect
- Analytics Manager/Lead
- Machine Learning Engineer
- Statistical Programming Specialist
Course Objectives
Data science is a fast-growing field, and proficiency in Python has become an essential skill across industries. This training gives you hands-on experience with the Python libraries used in real-world analytics work, along with practical skills you can apply from day one. Here's what the programme is built to deliver:
- Career Advancement: As demand for data professionals grows, a recognised certification can set you apart in the job market and add weight to your professional profile.
- Comprehensive Understanding: The curriculum covers the core concepts, tools, and techniques of the field, including NumPy, Pandas, Matplotlib, and Scikit-learn, so you can manipulate data, build predictive models, and visualise results with confidence.
- Hands-On Experience: You'll work on live projects using real datasets throughout the programme, building a portfolio you can show prospective employers.
- Personalised Instruction: Trainers provide individual guidance on data manipulation, visualisation, and machine learning, with feedback along the way to help you meet your learning goals.
- Flexibility: Sessions can be taken online at your own pace, with materials accessible anytime and trainer support available throughout.
Why is Python so widely used in this field?
Python's popularity comes down to its accessibility, its large developer community, and the breadth of libraries available for analysis and machine learning. It's a versatile language, equally suited to web development and scientific computing.
Combining strong data-handling capabilities with straightforward programming syntax is what makes Python such an effective tool for the work: manipulating large datasets, building predictive models, and visualising results, all supported by frameworks such as Scikit-learn, TensorFlow, and PyTorch.
