Data Analytics Course Enquiry Form
Data Analytics Course Syllabus
Learn Advanced Data Analytics
Introduction to Python
- Introduction to python
- Environment setup & start programming
- Python Conditional Statements, Loops and File Handling
- Core Objects and Advanced Data Structures; Functions and Lambdas
- The Object Oriented Side of it
Introduction to Data Analysis with Python
- What is data analysis?
- Overview of Python and its data analysis libraries (NumPy, pandas, Matplotlib, Seaborn)
- Setting up your Python environment
Data Preprocessing and Cleaning
- Importing data from various sources (CSV, Excel, SQL)
- Exploring and understanding the dataset
- Handling missing data: imputation techniques
- Dealing with outliers and anomalies
- Data transformation: normalization, standardization
- Data integration and manipulation using pandas
Exploratory Data Analysis (EDA)
- Descriptive statistics: mean, median, mode, variance, etc.
- Histograms, box plots, scatter plots
- Correlation analysis and heatmaps
- Univariate and bivariate analysis
- Data visualization using Matplotlib and Seaborn
Data Visualization
- Advanced data visualization techniques: bar plots, line plots, pie charts, etc.
- Interactive visualizations using Plotly
- Geospatial visualization
- Effective data storytelling and communication
Statistical Analysis
- Sampling techniques and the Central Limit Theorem
- Hypothesis testing: t-tests, chi-square tests, ANOVA
- Confidence intervals and p-values
- Interpreting statistical results
Machine Learning Algorithms for Data Analysis
- Introduction to machine learning
- Feature engineering and selection
- Linear regression: simple and multiple regression
- Logistic regression for classification
- Decision trees and random forests
- Model evaluation metrics: R-squared, MAE, RMSE, accuracy, precision, recall, F1-score
- Model assumptions and diagnostics
Time Series Analysis
- Introduction to time series data
- Time series components: trend, seasonality, noise
- Decomposition techniques
- Time series forecasting methods: moving average, ARIMA,
exponential smoothing - Implementing time series analysis in Python
Advanced Topics
- Dimensionality reduction techniques (PCA, t-SNE)
- Clustering algorithms (K-means, hierarchical clustering)
- Advanced statistical techniques (non-parametric tests, ANCOVA)
Real-World Projects and Case Studies
- Applying data analysis concepts to real datasets
- Solving data analysis challenges and problems
- Creating a portfolio of data analysis projects
Data Analytics Course Trainer Profile
Our Data Analytics trainer is a seasoned professional with 10 years of industry experience and currently serves as a Data Scientist in a leading MNC. Passionate about sharing his knowledge, he is delivering expert training in Data Analytics and python course for the past three years. His practical, hands-on approach ensures students gain valuable experience by working on real-world data science projects.
This Data Analytics Course is designed to give you practical training on real world projects.
Key Highlights of our Data Analytics Course
Hands-On Learning
We emphasise practical exercises and projects that allow you to properly apply your knowledge in real-world scenarios.
Industry-Relevant Tools
Gain proficiency in industry-standard data analysis tools, ensuring you are well-prepared for the job market.
Resume Building & Placement Assistance
We help our students in making professional resume as per industry standards. We provide 100% placement assistance.
Interview Preparation
Learn to handle interview. We prepare our students for interviews through interview focused sessions and mock interviews.
Overview of Data Analytics Course in Pune
Why join Data analytics course in Pune?
Data Analysts are the backbone of data-driven decision-making in the business world. They transform raw data into meaningful insights, helping organizations make informed choices. With the increasing importance of data in the IT industry, a Data Analytics Course at Tech Concept Hub in Pune prepares you with the skills to meet the on-growing demand for data professionals.
What is the prerequisite for a data analyst course in Pune?
The prerequisites for a data analyst course in Pune—or any location—depend on the institution or training provider. However, there are some common educational and skill-based requirements that most courses look for:
a. Educational Background:
- Minimum Qualification: A bachelor’s degree in any discipline (preferably in fields like Mathematics, Statistics, Computer Science, Engineering, Economics, or Business). Some courses accept students from non-technical backgrounds but may require additional preparation.
- Basic Knowledge of Mathematics and Statistics: Understanding concepts like mean, median, standard deviation, probability, and linear algebra is beneficial.
b. Technical Skills:
- Basic Computer Skills: Familiarity with using computers, file systems, and software applications.
- Microsoft Excel: Knowing basic functions, formulas, and data organization is advantageous.
- Programming Knowledge (Optional for Beginners): Familiarity with programming concepts, especially in Python or R, can be helpful but is not always mandatory for beginner courses.
c. Analytical and Problem-Solving Skills:
- An interest in analyzing data and solving real-world problems using logical reasoning.
Are there job opportunities for freshers after completing a data analytics course?
Yes, there are plenty of job opportunities for freshers after completing a Data Analytics course! As data-driven decision-making becomes integral to organizations, the demand for skilled data analysts continues to grow across industries. Freshers can secure entry-level roles provided they showcase their skills, knowledge, and project experience.
Entry-Level Job Roles for Data Analytics Freshers:
Data Analyst
- Responsibilities: Data cleaning, analysis, visualization, and reporting.
- Tools: Excel, SQL, Tableau, Power BI, Python/R.
Business Analyst
- Responsibilities: Understanding business requirements, analyzing data to provide insights, and bridging the gap between business and technology teams.
- Skills: Communication, visualization, and basic analytics.
Junior Data Scientist
- Responsibilities: Performing predictive analysis, building simple machine learning models, and deriving actionable insights.
- Skills: Python/R, machine learning basics.
Data Visualization Specialist
- Responsibilities: Creating dashboards and reports to present data insights.
- Tools: Tableau, Power BI, Excel.
Operations Analyst
- Responsibilities: Analyzing operational data to improve processes and efficiency.
- Skills: SQL, data visualization, operational metrics.
Market Research Analyst
- Responsibilities: Studying market trends, customer behavior, and competitors to guide business strategies.
- Skills: Data analysis, survey tools, Excel.
Reporting Analyst
- Responsibilities: Generating and automating reports for stakeholders.
- Tools: SQL, Excel, Tableau/Power BI.
Data Quality Analyst
- Responsibilities: Ensuring data accuracy, consistency, and reliability.
- Tools: SQL, Python, and data auditing methods.
How much salary can I expect as a junior data analyst professional?
As a Junior Data Analyst, your salary will depend on factors like location, industry, company size, your skills, certifications, and prior experience (if any). Here’s a breakdown of the typical salary expectations for a junior data analyst:
a. Salary Expectations by Region:
- Entry-Level (0–2 years of experience): ₹3,00,000 – ₹5,00,000 per annum.
- Top-Tier Companies or Skilled Freshers: ₹5,00,000 – ₹7,00,000 per annum.
b. Factors Influencing Salary:
Location:
- Salaries tend to be higher in metropolitan cities or tech hubs (e.g., Bangalore, Mumbai, Delhi in India; San Francisco, New York in the U.S.).
Industry:
- High-paying industries include Finance, Healthcare, E-commerce, IT, and Consulting.
Company Type:
- MNCs and Top-Tier Firms: Offer competitive salaries (e.g., Deloitte, PwC, Accenture, Google, Amazon).
- Startups: May offer slightly lower salaries but provide faster growth opportunities and diverse experiences.
Skill Set:
- Knowledge of SQL, Python, Excel, Tableau, or Power BI can fetch higher pay.
- Additional skills in statistics, machine learning basics, or advanced data visualization add value.
I am an experienced professional in the finance department, is a data analytics course suitable for me?
Yes, a data analytics course is highly suitable for you as an experienced professional in the finance department. Data analytics has become a vital skill in finance, enabling professionals to make data-driven decisions, optimize operations, and uncover insights that drive business growth.
Why Your Finance Background is a Strength:
- Domain Expertise: Your understanding of financial data and workflows gives you an edge in applying analytics effectively.
- Contextual Insights: You can interpret analytics results within the specific context of finance, a skill that other analysts may lack.
Career Opportunities Post-Course:
- Financial Analyst (with Data Analytics expertise)
- Business Intelligence Analyst
- Risk Analyst
- Investment Analyst
- FP&A Specialist (Financial Planning and Analysis)
- Finance Data Scientist (with advanced learning)
I am a fresher who recently graduated. Should I enroll in a data analytics course or data science course?
As a fresher starting with a Data Analytics course is often a better choice. It’s easier to transition into data science later, and analytics provides a strong foundation for understanding how data impacts businesses.
Data Analytics is about analyzing existing data to find patterns, create reports, and support decision-making. It’s ideal if you want to work in roles like Data Analyst, Business Analyst, or Reporting Specialist, where the focus is on understanding and visualizing data.
Data Science is broader and includes data analytics but also involves advanced topics like machine learning, artificial intelligence, and predictive modeling. It’s suitable if you’re interested in solving complex problems, developing models, and pursuing roles like Data Scientist or Machine Learning Engineer.
What is the difference between a data analyst and data scientist?
A Data Analyst focuses on analyzing existing data to uncover trends, generate reports, and provide actionable insights for decision-making. Their primary goal is to interpret data and present findings through visualizations and summaries. They often work with tools like Excel, SQL, Tableau, or Power BI and apply statistical techniques to solve business problems.
A Data Scientist, on the other hand, works on more advanced and complex problems. They use data to build predictive models, design machine learning algorithms, and explore innovative ways to use data for decision-making. Data scientists often deal with unstructured data, write code in Python or R, and use techniques from mathematics, statistics, and computer science.
In short, a data analyst extracts and interprets insights from data, while a data scientist creates models and solutions to predict or automate processes using data. Both roles are essential, but data science usually requires more technical and programming skills.
How much Python is required for a data analyst role?
For a Data Analyst role, you need a foundational understanding of Python. Unlike data scientists, data analysts typically don’t require in-depth knowledge of advanced programming concepts, but proficiency in certain Python libraries and skills is essential. Here’s a breakdown:
1. Basic Python Skills:
- Syntax and Basics:
- Variables, data types, loops, conditionals, and functions.
- File Handling:
- Reading and writing data from CSV, Excel, or text files.
- Error Handling:
- Debugging simple errors and handling exceptions.
2. Libraries to Learn:
- Pandas:
- For data manipulation (e.g., filtering, grouping, merging, and summarizing datasets).
- NumPy:
- For numerical computations and handling arrays.
- Matplotlib and Seaborn:
- For creating data visualizations like line charts, bar plots, and heatmaps.
- OpenPyXL or xlrd:
- For working with Excel files.
3. Data Cleaning and Transformation:
- Handling missing data.
- Removing duplicates, reformatting data, and applying transformations.
- Reshaping datasets (e.g., pivoting tables).
4. Data Analysis and Exploration:
- Calculating descriptive statistics (mean, median, mode).
- Understanding correlations and distributions.
- Generating summaries of datasets.
5. Optional but Useful Skills:
- Basic SQL Integration:
- Using Python to query databases via libraries like sqlite3 or SQLAlchemy.
- Regular Expressions (Regex):
- For text data extraction and cleaning.
- Working with APIs:
- Extracting data from APIs using libraries like requests.
How Much is Enough?
For a data analyst, you don’t need to master Python for machine learning or advanced algorithms. Instead, focus on data manipulation, cleaning, and visualization, as these tasks are integral to the role.
I want to change my career from data analyst to data science, what can I do?
Transitioning from a Data Analyst to a Data Scientist is a logical and achievable step since you already have experience working with data. To make the shift, you’ll need to expand your skills and knowledge to include more advanced techniques and tools used in data science.
Focus on developing a strong understanding of statistics, probability, and mathematics. These are critical for creating and evaluating machine learning models. Learn key algorithms and how they work, such as linear regression, decision trees, clustering, and neural networks.
Do I need to have a strong mathematics background to become a data analyst?
No, you don’t need a very strong mathematics background to become a data analyst, but you should have a basic understanding of key concepts. Familiarity with topics like statistics, probability, and basic algebra is essential because they are used to analyze data, find patterns, and draw conclusions.
For example, you’ll need to understand mean, median, mode, standard deviation, correlation, and regression analysis. These concepts help you summarize and interpret data effectively. Most of these topics can be learned as part of your data analytics training.
Advanced mathematics, like calculus or linear algebra, is not typically required for data analyst roles. However, if you plan to transition into data science later, those advanced topics may become more important. For now, focus on strengthening your skills in applied statistics and data visualization.
After completing a data analytics course in Pune, what certifications can I do to make my CV strong?
After completing a Data Analytics course in Pune, you can pursue a few key certifications to strengthen your CV. Here are some simple and impactful ones:
- Google Data Analytics Professional Certificate
- Covers the basics of data analytics, tools like SQL, Tableau, and R, and practical projects.
- Great for beginners.
- Microsoft Power BI Data Analyst Certification
- Validates your ability to use Power BI for data visualization and business intelligence.
- Highly valued in many industries.
- Tableau Desktop Specialist Certification
- Demonstrates your skills in creating interactive dashboards and visualizations using Tableau.
- SQL Certification (e.g., SQL for Data Science by Coursera)
- Proves your ability to extract and manipulate data using SQL.
- Microsoft Excel Certification (MO-200)
- Showcases your expertise in Excel for data analysis, a widely used tool.
These certifications are beginner-friendly and directly align with data analyst roles. Completing any of these will boost your credibility and make your CV stand out.
What is the impact of AI tools on data analyst job growth? Will the number of data analyst jobs increase or decrease in future?
The integration of Artificial Intelligence (AI) tools is reshaping the role of data analysts, enhancing efficiency by automating repetitive tasks and enabling deeper data insights. This evolution is expected to increase the demand for data analysts who are proficient in AI technologies. A survey indicates that between 2023 and 2027, 65% of companies anticipate that big data and AI will create jobs, while only 7% foresee job displacement.
Furthermore, AI is not replacing data analysts but augmenting their capabilities. Analysts equipped with AI skills can offer more value to organizations, leading to a growing need for AI-savvy data professionals.
In summary, the adoption of AI tools is poised to boost job growth for data analysts, especially for those who adapt by acquiring AI-related skills.
What makes Tech Concept Hub best institute for Data Analytics course in Pune ?
At Tech Concept Hub, We ensure that you stay updated with the latest IT trends, equipping you with both in-depth course knowledge and essential industry insights to stand out as a skilled IT professional, ready for top-tier opportunities. We are dedicated to offer training tailored to the industry’s needs. Don’t settle for just any Data analytics course—our program is designed to give you the competitive edge in the job market.
What sets Tech Concept Hub apart from other training institutes is our unwavering commitment to our students and our exceptional training quality. We are not just an institute but your partners on your journey to a successful IT career. Our trainers, who are highly experienced IT professionals, serve as mentors and guides, not just instructors.
Feedback from our students
Data Analyst Course in Pune FAQs
Why choose Tech Concept Hub for AWS course in Pune?
Almost every institute claims to have experienced trainers, every institute claims to provide practical training, every institute claim that their training is best. But what differentiates us is our commitment to help our students. We genuinely care for our students and it reflects in our reputation also (we have best rating on Google 4.9/5 based upon 850+ reviews).
Student’s career growth is at the core of our company. We do lot of due diligence in hiring our trainers. We hire only experienced trainers who are expert in their domain and have genuine passion for providing training.
In last 8 years, our training process is matured. We focus a lot on practical and do projects to make you job ready. Our classes are very interactive and encouraging. Learning is not just about covering course rather its about reasoning and cross questioning. At Tech Concept Hub in Pune, you don’t just cover Data Analytics course rather you learn data analytics.
What is the duration of Data Analytics course in Pune?
Duration of Data analytics course is 2 months. Each student has a different grasping power hence duration of Data analytics course might change little bit.
How much practical is done in Data Analytics course? Will I work on any project?
Our Data Analytics course in Pune is 80% practical. You will be doing real world project in Data analytics course. Our training program includes lot of assignments and project.
Does Tech Concept Hub provide online Data Analytics course?
Yes, Tech Concept Hub provides online as well as offline classes in Pune.
Does Tech Concept Hub offer institutional certificate after completion of Data Analytics course in Pune?
Yes, Certificate is issued after successful completion of course with all project work.
Does Tech Concept Hub provide Data Analytics course with placement assistance?
Yes, at Tech Concept Hub we have a dedicated placement team which ensures that students get access to latest job opening as early as possible.
Towards the end of Data analytics course, we help students make a professional CV. After that we conduct interview preparation workshops to prepare students for interviews. We also conduct mock interviews by industry experts who give valuable feedback for improvement.
What if I do not understand any topic, can I ask trainer to repeat the session?
We suggest students to participate in class actively. If something is not clear then raise your voice in class itself. We will appreciate this approach.
But getting doubts after class is very normal and it happens with almost every student. Feel free to ask questions in next session. Trainer will explain the topics again to help you understand the concepts and build confidence.
What if I miss any Live Class? How will I cover missed class?
Every Live class is getting recorded. In case you miss any class then you can watch recording of missed class and come back with questions if you have any. This happens with every student at some point of time and hence we give view access to recordings of class.
Data Analytics Course with Certification
Tech Concept Hub certification is highly valued by companies in India. It’s certificate increases the value of your resume. We provide certificate only after successful completion all projects and assignments.
Tech Concept Hub is having highest rating on Google among all training institutes in Pune. Companies across Pune and outside accept certification by Tech Concept Hub.